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Monthly Archives: May 2017

Standards in automation? There only one Lee in the IEEE...

May 27, 2017 | Phil Fersht


Few people can claim to have led shared services and IT for Kraft Foods, built shared services from scratch for Ascension Health, become one of the first true shared services practitioners to kick the tires with RPA... before establishing the industry's first standards body for Intelligent Process Automation with the IEEE.  Plus, he's going to be at our inaugural FORA Council (The Future of Operations in the Robotic Age) as the voice of standards and reason this September in Chicago.  Yes, ladies and gentlemen, meet the reincarnation of the process pontiff himself, Lee Coulter, who's going to give us a little more insight into why the heck we desperately need to adhere to some standards if we're going to find that automation haven that exists somewhere between fantasy, reality and failed promises...

Phil Fersht, CEO and Chief Analyst, HfS Research: Good morning Lee it’s great to chat with you again. You have been pretty deeply involved in developing and working on standards in process automation with the IEEE for over a year, would you be able to give us an update on what has been accomplished, and what we can expect next?

Lee Coulter, CEO Shared Services, Ascension Health and Chair for the IEEE Working Group on Standards in Intelligent Process Automation: Absolutely Phil, it has been quite a journey and I am very happy say that after working through the various societies of IEEE, the Board of Governors realised that this work impacted multiple societies and decided to use their reserve prerogative to sponsor a standards effort at the Board of Governors level. The first standard establishes some common terminology for us, it goes for approval on 5 May and that’s the procedural verification, making sure we have followed all the procedures of setting the standard, and we expect it to be published in June.  At the same time a part of IEEE called NASSCOM which stands for New Standards, is a committee that reviews all proposals. The next efforts, which will be referred to as P2756 in the IEEE world and their website, will be technology, taxonomy and classification for intelligent process automation products. Incidentally, in the same meeting where our first standard will be approved, they will also be reviewing and voting on the next standard. We have significantly increased attention for the second standard, which is really where we wanted to start but we realised we couldn’t do a taxonomy until we agreed what words meant. Several new members across the spectrum of providers have become advanced corporate members with IEEE and we expect to have a first working group meeting towards the end of June, as we go down the path of establishing a taxonomy.

Phil:  And when you look at the general state of automation in the industry today, where would you say companies are, as a whole, and how does this tie in with the need for standards?

Lee: It’s interesting, I recently presented an update at an event and a bunch of people hung out after the update, these were people new to the world of automation. They came up to thank me and I thought that was very interesting. I talked to some of them about their reaction to the material and it was very consistent with the frustration that led me to begin the effort in the first place. It is bewildering, and virtually impossible, to watch a presentation or listen to someone else speak, or read the marketing materials, or read any papers on the topic, because you don’t really know how to interpret what you are being told or what you are reading. We are finding that there is a great deal of interest in bringing some clarity so that we can have intelligent conversations. What continues to surprise me is how many organizations are just discovering this. You and I been talking about automation for four years, yet there are major Fortune 500 and Global 2000 companies who are hearing about it for the first time and just getting started. It’s interesting to think about the hype curve and the adoption curve in terms of where we are and I think we are just at the bottom of the hockey stick and it’s starting to become more mainframe. It’s a good time for the taxonomy and the standards to emerge as a large proportion of corporations across the world are entering this phase.

Interesting, I have been pulled into several rather vociferous conversations about whether automation was a prerequisite to artificial intelligence and cognitive, and various elements up the value chain, where as other people seem to talk about it as a mutually exclusive concept and framework.  How do you see this developing as you look at defining the space and is there a progressive step for companies as they get more experienced with automation? Or, do you think they need to have a different approach for both cognitive and automation?

Here’s the big dependency, the whole reason to do cognitive is for inline prescriptive analytics, so what does that mean, it means that on a real-time basis you have sufficient data for a cognitive system to identify, with high confidence, what is likely to happen and tell you what you need to do about it. Our discovery has been that when you look at the data strategies necessary to accumulate the right kind of data to feed these algorithms, automation is playing a key component in creating or illuminating the information necessary. Now is that to say that there are not potential transactional domains where you have sufficient information? I think that there are some pink unicorns out there, where an enterprise won’t naturally have all the data necessary. But, much like with standard process automation there are pink unicorns out there, big banks that had 2,000 people all doing loan apps, or credit apps, or mortgage processing, these were the pink unicorns. You could build three bots, copy and paste and have 600 bots running in the course of the year. For the rest of us, and for the clear majority of where you apply this stuff, this applies where there is a direct analogue between the pink unicorns and basic process automation into cognitive and the difference is all about understanding your data strategies and to build the data fabric you are going to need to feed your prescriptive analytic engine with. Our experience has been that absolutely, automation, is a prerequisite, and we have had to do a major transformation of how we capture and store data. We had to do a full re-platforming moving into Hadoop Cloudera-based data lake, as opposed to your standard data warehouse, those are just not sufficient to fuel these cognitive engines.

PhilNow as we look at the sheer noise around the industry – what do you think the gap is between marketing hype and reality? Is it 3 years, is it 5 years?  When we even hear Gartner drinking the Kool Aid, surely we need to close the gap a bit so people are getting into a more realistic mindset and road map?

Lee: Absolutely I would say that we are probably at the basics of RPA and RDA, we are probably 18 months, 24 months from a convergence. I think in the world of machine learning and cognitive we are probably still on a 3 to 5-year delta in terms of marketing hype. I’ll just give you a personal example of working with a cognitive service provider. It took us 9 months to get the statement of work and the KPIs in place to prove beyond a reasonable doubt that it was, in fact, machine learning doing the work, as opposed to data scientists and smart people doing stuff in the background. That was a wake-up call for us in terms of how far we are away. I was in a meeting, with a very large well-known provider of these kinds of services, and I told the guy to sit down and put his magic wand away because it’s not very magical and in fact it’s a huge order to get this stuff to produce meaningful value or meaningful work in the enterprise, and I am not going to listen to the marketing hype, we really need to get down to the business of figuring out how to get this stuff to produce value.  In a lot of cases, it’s expensive to dip your toe in the water with cognitive and even to get to, a proof of concept, proof of technology, proof of value. In one case we have been working on it for 15 months and we are just now beginning to see some progress. Coming back to your question, I still think we are 3 to 5 years away and I think we are going to see a convergence as big data, data services, data strategies and data science become far better understood as a necessary foundation to fuel the cognitive stuff.

Phil: Right... and who is going to work with clients to help them get there, Lee? Is it going to be the current crop of sourcing advisors? Do you think today's service providers have the right mindset and commercial models to get clients over the finish line, or do you think different players are going to emerge in the next 18 months?

Lee: That’s a fantastic question Phil, and here’s what I would tell you, what we are seeing is the current crop are not equipped to do this and there are a lot of one trick ponies out there. Process automation is great but the world of cognitive is a totally different domain, different skill sets, different technical competencies, and it’s far more IT intensive than process automation. There are some players out there, if they are smart about how they evolve their organizations and you could probably pick them out, these are people that not only provide advisory and consulting but also technology based solutions. I think they will have an upper hand in terms of being a credible guide, and advisor to buyers in this space, but I think for the folks that are really focusing on the basic process automation today, it’s going to take a significant re-tooling to move into being an advisor in this cognitive space.

Phil: Final question, Lee... if we were to anoint you the ‘King of Automation’ for one week and we granted you one wish, what would that wish be?

Lee: It would be to solve my data needs. Everywhere we look we are finding that access to data, transitional state data, illuminating dark data, information converted into data, or vice versa, it’s one of those things – if I could solve that, then all sorts of horizons open up on the cognitive space and we are finding out that’s just a journey where you fix a few things, you try again, you add some more, you try again. There doesn’t seem to be a well-understood approach about how you think about a knowledge domain and what data you need to make it work, so if I had one wish, and I could rub the Genie’s lamp, then I would want to solve my data needs.

Phil: Thank you very much, great answer, Lee :)  You've been a great friend to HfS and am sure many of the folks reading this are looking forward to seeing you at the FORA inaugural session in Chicago this September (see link for more details).

Posted in: Robotic Process Automation

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Blockchain’s Potential To Overturn The Way We Operate The BackOffice

May 26, 2017 | Christine Ferrusi Ross

My colleague Steve Goldberg recently wrote about artificial intelligence finally getting incorporated into payroll processes. And I recently spoke with IBM about how they’re working to reinvent finance processes using blockchain. Intra-company processes present an interesting use case for blockchain, although they don’t actually have many of the common characteristics of the most popular use cases. Why?

Typically, we talk about blockchain being best for processes and operations where there is:

  • Low trust among participants
  • Lower existing technology investments
  • Low transparency or visibility into the process
  • Long cycle times in completing transactions

In contrast, finance and HR tend to be:

  • Medium to high trust (business partners tend to be known and therefore trusted by finance, for example, and certainly employees are known and vetted by the employer)
  • Relatively strong on investment in technology (although worse for HR than finance)
  • Decent transparency for internal aspects of the processes, but still poor for the parts of the process that interconnect with third parties – such as purchase orders, confirmation of delivery of products/services, etc. Transparency of data is less in HR, where the data starts at the individual level and then rolls up to the divisional and corporate levels.
  • Respectable cycle times for transactions. Understanding that companies always want to close the books faster, etc., cycle times aren’t as bad for internal processes as for multi-party processes.

So, if finance and HR don’t meet the general criteria for blockchain use, why would companies consider it as a viable option? We recently heard from IBM and Infosys about blockchain’s potential in finance, and our other research also shows the following likely benefits:

  • Security. A blockchain-based application tends to be more secure. Currently, it’s considered impossible to hack the data in a block, although it’s possible to hack at the edges, such as someone’s access point. However, the security for blockchain transactions and recording are much better than many of the systems companies use today. Consider the risks of letting employee or applicant data being hacked and blockchain becomes more attractive.
  • Immutability. When transactions happen quickly and permanently, then companies reduce the likelihood of duplicate payments for the same invoice and double spending (using the same money twice because it looks like it’s still available for a period of time after it’s actually been spent.) It also helps with employee data such as payroll information and benefits distribution.
  • Smart contracts. The business logic of transactions can be encoded into a blockchain app so that the rules get implemented automatically, taking out human error and increasing the accuracy of the transactions. For example, a contract between a client and a materials vendor can be coded into a blockchain, then the payment of the invoice gets made automatically after data about the materials’ quality, timeliness of delivery, and other terms of the agreement are incorporated.
  • Speed. While finance processes are ok today, any increase in speed helps the company. For example, if international payment transactions can be shortened, it improves the company’s operating margins by getting revenue quicker. The speed improvements will be particularly noticeable in processes that touch third parties.
  • Auditing and compliance. When the data are in a blockchain, there is complete transparency of that data. As a result, searching for records and validating data in order to audit and prove compliance becomes a faster and more accurate effort. Many believe that the reduction in cost and time of auditing and compliance are enough to justify the investment in blockchain for the back office.

Also, it’s important to note that we’re not advocating replacing ERP and other systems right away – you can record data on blockchain without doing the transaction on the chain. So in the interim blockchain can supplement rather than replace.

Bottom Line: Back-office processes may not be as world-changing as other blockchain use cases, but there is still significant potential for finance and HR to get reinvented with the technology.

Posted in: Blockchain

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How EXL is taking a “grassroots” approach for incremental digital transformation - for itself and clients

May 25, 2017 | Barbra McGann

EXL is going broad and deep from its core strength in analytics. At its recent EXL Client, Industry Analyst, and Advisor Day, the service provider showcased its theme of “Accelerating Digital Transformation” driven by “look deeper” with analytics.

We heard from both EXL and clients during the day that while clients appreciate that “digital” can help “transform” their staid businesses into one seamless capability that is more flexible and responsive, it doesn’t feel real or short-term. Their businesses are too siloed, risk averse, and focused on the day to day. The sense I got from the day was that EXL is “right there” with its clients facing these challenges – meaning, it is not behind, and it is not way ahead and looking over its shoulder. EXL is working shoulder to shoulder with its clients -- at the grassroots level-- to figure out the vision for a more customer-centric, insight-driven, and agile business, map it out, and take the steps to get there. The service provider is doing this by keeping its focus on the core strength of analytics, and addressing gaps it has had in data management and automation in particular.

 

The front office is only as effective as the middle and back allows it to be

EXL’s traditional strength is in the middle office with industry-specific services support and analytics and in the back office with finance & accounting BPO. The front office cannot be effectively customer centric—responsive and personalized—if it doesn’t have a flexible data infrastructure through this middle and back office to drive context and act with speed, precision, and fluidity. EXL is working with clients where it sits – in that middle and back office, particularly in insurance, healthcare, and financial services.

For example, with one client that started as a headcount-based cost reduction BPO play in F&A, EXL proposed a number of workflow process and “digital” enablers such as RPA and chat to have a more interactive and responsive function. The client has been able to remove itself from a fairly heavy-handed “oversight” of the day-to-day and EXL has been able to find and implement efficiencies for faster processing, fewer errors or points of confusion, and greater satisfaction all around. A key solution element here was the human-centered approach: the team took the time to interview people involved in the current process at the client and at EXL, understand what was not working, and design and test out solutions that were people, process, and technology oriented (a.k.a. design thinking).

Building out the data chain

Over the past couple of years, EXL has hired, acquired, and developed a broader spectrum of capability in analytics modeling and reporting to build out this core strength. It’s been a differentiator for execution, but not across the full analytics spectrum and not at scale. Now it’s expanding upstream into data and data management, built-in proprietary technology and partnerships for “bots,” and supplementing the shift through its data acquisitions such as RPM Direct and Datasource.

Its viewpoint of the impact of data and analytics was demonstrated through an example in the middle office of an insurance client. EXL created a digital interface for customer acquisition, combined it with its LifePro policy admin system and data analytics. The client uses the database to target and segment customers for campaigns. Interested customers can use mobile or internet portal access to apply. Based on the back end integration with the underwriting and pricing engine, the customer gets a quote and the company can bind the policy online.

The role of robotics

The conversation around robotic process automation and artificial intelligence (the latter less of a focus and still a point of view to be developed, it seems) is constantly tied to analytics.  EXL’s observation is that “clients now seem to be taking a more pragmatic approach to intelligent automation” – how to institutionalize it, not just use it. One client example was of setting up a COE in a “build, operate, transfer” approach where EXL initially builds out the automation strategy, governance, use cases, service orchestration layers and bot skillsets. If you are interested in this approach, it’s one that we haven’t heard quite as clearly articulated from other service providers, and an area that we do hear is a challenge for global business services centers, for example. Some companies like Ascension Health and SEI Investments have to take the leadership on their own, but others may appreciate this kind of support to get RPA not just used but infused into the organization. I do get the sense this is a newer offering for EXL, so do your due diligence on the availability of skills and capabilities across different suites, but we often hear from clients that EXL makes a responsive, transparent partner.

Another place EXL is building scale is in its library of function- and industry-specific bots and partnerships with third parties including WorkFusion, Automation Anywhere, and Blue Prism. With automation, the service provider is willing to guarantee productivity and cost benefit, and change the traditional BPO engagement model. As you consider how you want to partner with EXL, take a look at its bot library, its subject matter experts, and consider the balance with your own capabilities. When you look at solving a problem and impacting an outcome and then designing the solution in between, rather than the previous outsourcing approach of lift and shift, you have more flexibility in your business.

Bottom line: Rethink your partnership style and challenge EXL.

Tap into these areas where it is investing: analytics; platform-based services; “advanced automation”; and human-centric digital transformation.  What to watch: the need to scale in these focus areas and become a more credible powerhouse in consulting to lead the charge.

Posted in: Design ThinkingDigital Transformation

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Another “SRO” Crowd for an AI Presentation, But at a Payroll Conference?

May 25, 2017 | Steve Goldberg

This standing room only crowd for an industry conference’s AI session, something seen with great regularity these days, is actually from last week’s American Payroll Association event in Orlando. You read that correctly.

While the payroll function and services market likely weren’t among the first AI or RPA candidates written on white boards in innovation labs, this obvious level of interest might suggest a “can’t see the forest through the trees” dynamic operating in some of those innovation labs. Back-office corporate functions such as payroll are in fact fertile ground for RPA and intelligent automation overall, given the preponderance of recurring manual tasks and transactions not dependent on person-to-person interaction.

Innovation labs are now on the case.

The speaker for this session called “Prepare Your Teams for the Future of Payroll: Robotics, Automation & Shared Services” was Brian Radin, President of global payroll services provider CloudPay and long-time entrepreneur in the HR Tech space as well. Brian immediately got everyone’s attention by factually reporting that the number of bank teller jobs did not decrease in the years following the introduction of ATM machines. Teller numbers actually went up due to shifting staff costs to support new, higher value services within retail branches, which ultimately allowed more local branches to open up, tellers in tow.

Using AI in the realm of HR operations, including cognitive computing and RPA (Robotic Process Automation) or bots, has been explored in my blog posts and also a recent POV. Radin’s session focused specifically on AI’s current and future use in payroll operations, including via services providers like CloudPay and over a dozen others to be profiled in my HfS Blueprint Report “Payroll-as-a-Service: 2017” (published this July).  

Some Easy Questions, Some Hard Ones

Radin’s talk directly addressed some key questions about “AI in Payroll”; e.g., how can (or will) these capabilities help payroll clients spend less time on manually intensive, routine or recurring tasks, ones that machines can often handle with more alacrity? And are there other tasks where resourcing can be toggled between human and bot staff depending on availability? Here the presenter highlighted examples like data validations and checks pre and post-payroll run (payroll has quite a few of those), machines fixing errors or automating the consolidation of data, and of course, chatbots to answer recurring questions like “what is my accrued PTO?” or “when will I receive my first check?” (Questions which come up hundreds of times per year.) Allowing RPA tools to handle these will benefit clients of providers like CloudPay and any other vendor investing in these capabilities. And as far as highlighting a “resourcing agnostic” (bot or person) type of activity in payroll, the example given was using people or bot staff to train new staff.

One of the highlights of the session for me was listening to questions attendees were posing at the podium afterward, away from the large audience. One gentleman told Radin that training and re-skilling of staff were already going on in his company in areas where RPA would be heavily leveraged, but it sometimes provided only a year or so of “job runway” for employees until RPA would impact their next job. Then re-skilling would have to start again. Radin’s response was both admirable and accurate: “Re-skilling decisions in the RPA era is very much a work in progress.”

Machines that Do, Do and Think, and Learn

CloudPay’s VP Marketing, David Barak, elaborated for me after the session on Radin’s slide which highlighted these three different categories of RPA capabilities: “Do” describes the use of RPA to move and manipulate payroll data without human involvement, as one example. “Do and think” capabilities include the machine flagging and fixing hundreds of data issues pre-payroll run; and while “Learn” is an RPA capability in payroll processing that’s still being tested and improved upon (as with machine learning in most areas), it includes anticipating spikes in payroll processing costs based on time of year, business cycles, new regulations, etc. This information can then guide the customer in optimizing staffing levels.

Bottom Line: Payroll departments and services provider clients will increasingly benefit from emerging RPA and cognitive capabilities. It will probably be a few steps forward and a couple backward until something akin to a “human/bot hybrid resourcing homeostasis” is figured out – in general, and also reflecting specific customer contexts. Predicting how far / how fast with any precision, in any industry or discipline, is almost a total crapshoot. One thing we do know, machines are not nearly as susceptible to errors due to work overload or distractions.

Posted in: Digital TransformationHR Strategy

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Recessions destroy jobs not robots

May 24, 2017 | Jamie Snowdon

May is one of my favourite months of the year. Not because it warms up and brings milder weather. Not because of the number of bank holidays we get in the UK or that it is National Burger Month or National Innovators Month (who decides these?) – but because of the massive amount of data that becomes available during the month. It marks when most of the annual reports are available, and importantly it marks when National Bureau of Labor Statistics publishes its annual occupation statistic for the US. If that isn’t exciting, you clearly aren’t a data junkie like me ????

These statistics are important as they show real job creation and job losses – which comes as a refreshing contrast to the recent obsession we see around the prediction of mass job losses caused by digital and the shift toward more digital operations. This rhetoric is becoming increasingly unhelpful as enterprise organizations navigate the ongoing shift toward digitally engaged commerce. The current mantra de jour being advances in machine learning, the internet of things (IoT), data analytics, and artificial intelligence (AI) will steadily eliminate all kinds of jobs. Economies across the globe will have to brace themselves for massive job destruction.

We’ve all seen the studies that state that half of manufacturing jobs will be eliminated by automation in the next decade. Driverless trucks and trains are set to become commonplace, eliminating many more jobs. Advances in technology are not only impacting lower skilled jobs but also skilled professions. People with advanced qualifications such as lawyers and doctors are undertaking activities that can be automated.

Although there is some truth in this – technology is taking on increasing amounts of low skilled and mundane work, the largest inhibitor to the continued digital transformation of businesses and whole industries is, and will continue to be, a lack of skills. Yes, it is a shortage of talent that will slow down the adoption of new technologies such as robotics, AI, big data analytics, and the IoT.

The truth as you can clearly see below, automation doesn’t kill jobs – wider economic issues kill job creation – recessions and stagnation. As you can see from labor statistics in the US – in spite of the growth of automation there is still a net gain in jobs over the last 5 years:

Although automation will impact jobs, the rate at which jobs will be eliminated will be limited by the availability of skills that can implement and manage this technology. Which tends to self-regulate the creation v destruction trend and help, at least with the timing of any job market adjustment. As we have seen in past industrial revolutions, these shifts in jobs end up creating more work than they eliminate. We saw in the 18th century industrial revolution massive shifts from agricultural work – we expect a similar trend with this current wave of disruption.

New jobs will need to be created to enable automation, and to engender the innovation facilitated by new technology. Skills required for these new jobs are in extremely short supply. We maintain that a lack of people with appropriate skills, will slow any shift in operating models toward driverless trucks, driverless trains, software defined factories, connected health, smart grids, smart cities and so forth.

So what will these new roles be?

The biggest change will be a shift from specific functional roles to more blended multilayered job. With more complex skill sets being required. Organizations will need to acquire talent which blends technical skills with operational skills (industry specific skills) as well as softer skills such as critical thinking, adaptability, continuous learning, active listening and other non traditional capabilities. Education and training from technology professionals needs to be much more holistic, given that technology is transforming many aspects of our lives. With education and training institutions having to adjust offerings so they develop the required blended and holistic skill sets for the needs of the emerging job market. These new jobs emphasize skills, knowledge and willingness to learn, over traditional highly specialized degrees, and the rather narrow scoped careers that gave people their early work experience.

Valuable workers will soon be those who can adapt and learn new skills as and when more automation is embedded within their role. To stay ahead in the talent game, businesses should focus on:

  • Hiring for potential. This means hiring staff based on their inherent ability to learn and adapt to situations rather than their experience, particularly if it is narrow.
  • Learning not education. These two things are not the same – if you hire people who are able to learn, you must provide a continuous learning environment and incentives based on learning. Just hiring people with Stanford or Harvard degrees won’t necessarily give you people who are able to learn on the job long term.
  • This means looking outside of the norm when hiring. Traditional MBA courses may not provide you with people who have flexibility to operate in today’s multidisciplinary world.
  • Work with external education establishments to make sure students have the skills you want. Better to invest in helping universities develop the skills you need in people rather than focus on competing for them. Demonstrating a willingness to invest in young people is likely to engender loyalty and being part of university programmes provides more opportunity to demonstrate that commitment than the usual milk round and job fairs.

The Bottom Line – We must focus on generating value for customers, not protectionism and panic-mongering

There needs to be a shift in emphasis away from set task based skills to more blended and soft skills where technical and business skills combine. Without an increase in the supply of these kind of people the transformation to more digitally driven operating models will be slowed. Hiring policies need to look to the future, without the right people the step into the digitally enabled world will slow to a crawl.

It today's swirl of gibbering noise around the social media presses, it's the responsibility of leading analysts, advisors and academics to be the voices of sanity and reason, when it comes to topics as critical as the future of work elimination through Intelligent Automation technology.  The automation vendors love the hype as it gets them attention with clients, but analysts who like to take money from these vendors have a responsibility to articulate the realities of these technologies to their clients. They are great at augmenting work flows, and even aiding medical discoveries, but this is the real value - it's not about sacking people.  It's about making operations function better so people can do their jobs better.  The real "roboboss" is the human enterprise operator who can use smart Intelligent automation tools to enhance the quality of their work.

Net-net, industry analysts, advisors, robotics vendors, academics and service providers need to engage with clients around how all these disruptive approaches will affect talent management as well as organizational structures. Even without these apocalyptic scenarios, some job functions are likely to either disappear or be significantly diminished (as our automation job impact forecast reveals). Equally, we need to talk about governance of these new environments, touching upon ethical, but also practical, issues. This is not only a necessity for the broader adoption, but also offers high value opportunities. 

Posted in: Robotic Process Automation

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Gartner: 96% of customers are getting real value from RPA? Really?

May 23, 2017 | Phil Fersht

Last year we couldn't help ourselves revealing our lovely Gartner analyst friends, via the voice of Chief of Research and Distinguished Analyst, Fran Karamouzis, declaring, "3 million of us will be supervised by robobosses by 2018".  

So, while many of us are counting down the last few months enjoying our last experiences of having human bosses (or maybe some of us will actually prefer a robot), we can now breathe a huge sigh of relief that a whopping "96% of clients are getting real value from RPA" (Robotic Process Automation).  And not only that, RPA is thriving at a "satisfaction level greater than anything Fran has seen in her 17 years at Gartner":

I personally would love to meet this incredible cross sample of delighted clients Fran has had the good fortune to interview, seeing as we've been covering the emergence of RPA for nearly 5 years and this space is still at a very early phase of (sometimes) painful RPA experimentation, as enterprises figure out how to scale these tools, govern them and learn how to integrate them with other applications using scarce technical skills, while dealing with very challenging change issues.  

At HfS, we just came off a very intense day with 60 enterprise clients tinkering with RPA, and can officially declare that 96% of them are definitely not in love with their experience.  In fact, only a handful are making real progress, while the majority lack a cohesive governance program to get this stuff working on even a few rudimentary processes.  At HfS, we estimate, from our extensive ongoing research, that about half of today's RPA implementations are, so far, making some progress, while even Ernst and Young's new RPA report declares it has seen 30-50% of initial RPA implementations fail.   

Why claiming 96% of RPA customers are seeing real value is plainly ridiculous 

Several of the RPA solutions vendors are painting an over-glamorous picture of dramatic cost savings and ROI. RPA software firms are claiming - and demonstrating - some client cases where ~40% of cost (or more, in some cases) is being taken off the bottom line. While some of these cases are genuine, there are many RPA pilots and early-phase implementations in the industry that have been left stranded because clients just couldn't figure out the ROI and how to implement this stuff. This isn't simply a case of buying software and looping broken processes together to remove manual efforts... this requires real buy-in from IT and operations leaders to invest in the technical, organizational change management, and process transformation skills. 

Several RPA clients cannot scale their solutions and are aborting implementations.  One solution in particular, which featured high in many analyst scatterplots, has recently suffered

Read More »

Posted in: Confusing Outsourcing InformationRobotic Process Automation

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Here Cometh Cognitive Procurement with SAP Ariba and IBM joining forces

May 17, 2017 | Derk Erbé

We are now seeing real commercial business applications getting serious about their cognitive potential, with the new announcement of SAP Ariba and IBM joining forces to cognify contracting and sourcing processes, as a start. At HfS, we believe this is just the start of core business applications being immersed in cognitive capability to deliver a new threshold of business value for enterprise clients.

In the recent HfS Procurement As-a-Service Blueprint, IBM, an HfS Winner’s Circle industry leader, invested in transformation-led delivery with a ‘Consult to Operate’ strategy, focusing on on-demand consumable digital processes for procurement fueled by analytics and cognitive.

Looking ahead to 2020, HfS recently wrote: "Towards 2020 IBM will be leading in the cognitive procurement services space. Underpinned by a strong BPaaS platform, most clients will look at IBM first when it comes to new cognitive technology-driven services with vastly improved data analytics capabilities. The biggest challenge for IBM to succeed with cognitive procurement is to bring clients along this journey".

The goal of this partnership is to take cognitive procurement to the next level. SAP Ariba and IBM are creating two centres for Cognitive Procurement, in Palo Alto and New York. The cognitive procurement capabilities will be expanded through a joint go-to-market strategy and a joint development roadmap. But there is more to this deal… 

"Making procurement awesome on steroids"

Asked what the biggest benefit of the partnership is, Moray Reid, IBM Procurement's Global Offerings Leader, took SAP Ariba’s motto up a notch; "Make procurement awesome on steroids”, by really bringing leadership to the procurement space and enabling smart new technologies to allow customers to make better decisions in real-time. SAP Ariba and IBM truly believe this is a case of ‘better together’.

In a recent article - 'What will The Procurement As-a-Service Provider Landscape look like in 2020?’ - HfS wrote, "IBM has a massive supply chain, which it smartly leverages in its procurement offerings. IBM is bullish on cognitive procurement. IBM BPS is morphing into Cognitive Business Solutions. Its own procurement provides a great playground for applying and road testing all the new cognitive procurement solutions, giving it an advantage over providers who don't manage procurement for their own organization or have less 'cognitive savvy’ clients”.

The partnership with Ariba is a serious step forward for the cognitive procurement ambitions of both organisations. SAP Ariba is a dominant player in the procurement space, with a mature, horizontally integrated platform, the world’s largest business network and end-to-end suite of source-to-settle applications that cover all categories of spend. SAP Ariba and IBM are developing the first cognitive use cases together and creating new services, adopting IBM’s Consult to Operate model, leveraging consulting capabilities in operations to deliver value on an outcome basis. One of the use cases under development is in contract intelligence; Watson sifting through structured and unstructured contract data to gain insights and improve contract compliance, a big step towards actually achieving benefits, one of the toughest challenges in procurement. Part of the work will further the development of intelligent procurement solutions and services, with IBM and SAP Ariba working side by side to explore applications of emerging technologies, including blockchain.

What’s in it for SAP Ariba?

SAP Ariba needed a new differentiator as competition is heating up and competitors, like Tradeshift and Coupa, accrue assets and client wins. With SAP Leonardo alongside Watson, it gets a credible cognitive engine. Further, to leverage network effects and grow its value, the network needs to expand by adding more suppliers. Bringing IBM’s huge supplier base on board will boost the value of the Ariba Network increasing its size and scale.

What’s in it for IBM?

Emptoris has been a good foundation for IBM’s procurement services and BPaaS delivery, but lacks the network. Instead of betting on two horses, by continued development of Emptoris for internal use and partnering to provide the business network capability to clients, IBM will, over the coming period, transition all its BPaaS offerings to SAP Ariba. This is a big operation, but it makes a lot of sense. There must be hard assurances and safeguards in the partnership agreement, otherwise it’s a risky bet to put your As-a-Service/BPaaS future in the hands of a partner.

Competing on multiple fronts

Watson is IBM’s big platform bet of the decade – its main challenge is being a bit too far ahead of its time, pushing a cognitive story at clients that simply are too bogged down in other initiatives to take the time and consider the ROI of injecting cognitive capability into their processes. Positioning it as one of the largest procurement platforms makes a lot of sense from the perspective of not only competing for Procurement As-a-Service services with other providers, but also allowing IBM to be a technology provider to competitors via SAP Ariba. If you can’t beat them on the services front (you can’t win them all), at least get a piece of the action via the procurement platform side.

What’s in it for buyers?

Many buyers see cognitive procurement as the next frontier, but don’t have a clear understanding, or plan, on how to make it work for their organisations; the majority of procurement organizations perceive themselves as far removed from advanced innovative procurement capabilities. They are fixing the basics, getting procurement technology to work and pondering the opportunities RPA could bring the procurement function. The gap between cognitive procurement and the (perceived) level of maturity and change readiness of procurement is the hurdle IBM needs to take to make its cognitive ambitions reality or be at risk of running too far ahead of the game.

IBM and SAP Ariba will focus on a step-by-step approach to ease clients into the world of cognitive procurement, the key being small steps with tangible benefit. Buyers who need to see a serious roadmap and a partner with deep domain expertise and consulting capabilities gain a valuable option for their journey to the future of procurement.

Questions left to be answered

How will other partners react? Eleven out of fifteen service providers in the 2016 ‘Procurement As-a-Service Blueprint’ have a partnership with SAP Ariba. Just as when Wipro announced its strategic partnership and investment in Tradeshift earlier this year, the SAP Ariba and IBM folks will be fielding a lot of calls from concerned partners. What will this mean for their partnership with SAP Ariba, IBM or both? How much influence and access will IBM have on SAP Ariba’s architecture, roadmap and governance? How valuable is our partnership to SAP Ariba, now IBM stepped to the plate in such a manner?

The bottom-line: Procurement buyers; there is light at the end of the cognitive procurement tunnel

Two giants putting their weight behind cognitive procurement is a big step in taking the promise of cognitive into the realm of procurement.

Hand holding will be required to take clients along the journey and IBM and SAP Ariba vow to be the ones to extend their hand.

HfS will closely follow the value this partnership will create for service buyers, particularly in the fields of strategic sourcing and category management. How will those upstream procurement areas benefit from the cognitive capabilities on top of a business network? Can it find clever ways to address the scarcity of category talent and expertise? Is this partnership bringing true digital procurement closer, with pulling more suppliers onto the digital platform than before?

Focusing Watson on processes that can significantly benefit from tangible cognizant results, especially areas like contract management and general sourcing, is a smart way forward.  HfS expects IBM to follow this with other initiatives across other business processes where the firm has real strength and depth, such as HR and F&A – and eventually broader supply chain.  We should also expect further forays of Watson in the healthcare sector, where IBM has proven credibility supporting medical research and life sciences work (see our earlier report on Watson’s potential in medical research).

Posted in: Cognitive ComputingProcurement

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Facing A Perfect Storm of Disruption. How is the Utility Industry Dealing with Existential Challenges?

May 17, 2017 | Derk Erbé

In the HfS Blueprint Report for Utility Operations, we take a close look at how you can better find support for business model creation, IT/OT integration and customer experience improvement in engagements.

Electricity is the lifeblood of our economy and society. Electricity is what makes your smartphones, computers, TVs, refrigerators, and lamps work. Many core processes in our lives and businesses are electricity dependent, and electric appliances are everywhere. Gas, coal, oil, nuclear, water, wind, and sun – all of these resources are used to power the grid, the world’s largest machine and one of the humankind’s greatest engineering achievements. And today’s infrastructure is overwhelmed.

The current infrastructures are built for a bygone era. Utilities need smarter and seamlessly connected grids that allow renewable production and local energy generation. The emergence of micro-grids and residential- and utility-scale battery storage for electricity, for example, will give a push to local energy systems. But, integrating all these new technologies, building new business models around them and improving customer experiences require utilities to drastically change its way of working. This is where smart utilities leverage service providers.

Employing Utility Operations services to get ahead of being disrupted

The HfS Research Blueprint Report for Utility Operations provides a comprehensive overview of services for the utility industry. This Blueprint looks at business process services, information technology services, and engineering services across the utility value chain areas of generation, market operations, transmission, distribution and metering, marketing and retail, and cross-value chain BPO, engineering, and ITO services.

This report analyses and reviews how the market is evolving toward more business-outcome focused, flexible, and collaborative services and how service providers are (or are not yet) meeting the needs of utility organizations. It also includes profiles and assessments of 14 providers of Utility Operations services.

Top challenges include: 

  • Modernizing the power infrastructure to support renewable integration and optimization 
  • Leveraging digital in the grid infrastructure
  • How the power generation fuel mix changed for good
  • Changing customer expectations
  • Disruption of business models
  • New competitors enter the arena
  • Cybersecurity: of paramount importance, but still often overlooked

These challenges underscore three key market dynamics:

  1. Utility Operations services adoption accelerates. The market is vibrant and in growth mode, with several service providers reporting high growth rates for their Utility practice, outpacing other horizontal and vertical practices. This strong growth is a sign of an industry pulling the services lever hard to make up for lost ground. Having been reluctant and conservative about investments in technology and now, in the face of so much disruption and technology-driven opportunities, utilities are partnering with service providers to catch-up. For their part, many service providers have started to strike the right cord with a mix of outcome based services, partnerships, strategy and messaging around technology-driven areas like smart grid, smart metering, renewable energy integration and intelligent automation.  There’s a refresh underway for partnerships in this market.

  2. The value of partnerships. No one company can deliver all the services and solutions required for the transformation the utility industry is experiencing. In the digital age, breaking down silos, creating end-to-end processes and information flows, and unleashing the actionable insights derived from advanced data analytics are critical imperatives for survival. We see this in the convergence of operational technology (OT) and information technology (IT) and in the increasing role of digital platforms across the value chain. Leaders in the utility industry are forming partnerships as brokers to find and bring together the best capability to impact. Examples are utilities that partner with service providers and Original Equipment Manufacturers to create resilient, autonomous, solar micro-grids incorporating equipment, battery technology, sensors, analytics and on-demand services. The result is a resilient emergency demand response solution.

  3. Plug-and-Play services emerge. We see interest emerging among service buyers for plug-and-play digital business services, particularly for analytics and retail platforms. These modular, on-demand services give utilities the advantage of easy implementation and the ability to tap into a business outcome, increasing speed to value. Plug-and-play services are in the initial stage of development with significant progress forecasted over the next few years as service providers become more comfortable with being platform developers.


Bottom Line: Utility executives, you will find guidance in this report to reinvent customer experiences, processes and operating models, and to tap the unmatched potential of renewable energy, digital technologies, and storage.

The challenges outlined in this blog and the Blueprint report form an existential threat to the utility industry as we know it. Utilities must face these challenges head-on or risk becoming irrelevant, with others - new entrants or savvy current competitors - taking its role in the value chain and its customers. The service providers in the Utility Operations Blueprint are reliable options to partner with and charge ahead together.

HfS Premium Subscribers can click here to download your copy of the new 2017 Utility Operations Blueprint Report. It includes coverage of the following service providers: Accenture, Atos, Capgemini, Cognizant, Cyient, EXL, HCL, IBM, Infosys, Luxoft, TCS, Tech Mahindra, Tieto, Wipro.

Posted in: Utilities & Resources

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The FORA Council has assembled the industry's leading minds in cognitive automation

May 17, 2017 | Phil Fersht

When an industry is enduring a secular shift that is literally redefining how we do work, it's pretty important to get some real, unfettered dialog going among all the key stakeholders this impacts. We need to break free from the glitzy paid-for sales presentations, robot keyrings, stress balls, nasty logo-ed leather notepads and greedy events firms vying for a quick buck from vendors eager to part with cash to promote themselves to all their competitors.

That's why we're assembling 75 of the industry's finest leaders in a single room for a whole afternoon to thrash out the mandate for the future of operations in the robotic age for our inaugural FORA council session in Chicago, 19th September.  And promise no sponsors, stress balls or bad white papers to take away...

Here's just a sample of the industry robo dignitaries who've already committed:

  • Alastair Bathgate, CEO, Blue Prism
  • Chetan Dube, CEO, IPsoft
  • Chip Wagner, President, Emerging Business Services, ISG
  • Cliff Justice, Partner, US Leader, Cognitive Automation and Digital Labor, KPMG
  • David Poole, CEO, Symphony Ventures
  • Jesus Mantas, Managing Partner and General Manager, IBM Business Consulting, IBM US
  • Lee Coulter, Chair for the IEEE Working Group on Standards in Intelligent Process Automation
  • Dr. Mary C. Lacity, Curators' Distinguished Professor of Information Systems, UMSL, and Visiting Scholar MIT
  • Max Yankelevich, CEO, WorkFusion
  • Mihir Shukla, CEO, Automation Anywhere
  • Peter Lowes, Partner, and Head of Robotics & Cognitive Automation, Deloitte US
  • Shantanu Ghosh, SVP, CFO Services and Consulting, Genpact
  • Thomas Torlone, U.S. Leader of Enterprise Business Services, PwC
  • Weston Jones, Global RPA Leader, EY

We also have leaders of cognitive and automation initiatives from the following buyside firms already signed up to get stuck into the debate:

So let's cut to the chase - it's time to have the real, hard conversation about where we really are as an industry. Why aren't those 40% cost savings happening, each time someone slams in some software and hope it somehow eliminates manual labor because they can access a bot library? In fact, why are a third of RPA pilots just left hanging with no result?  Yes, people, it's time to wake up and smell those robotic roses and have those really tough conversations about what is real, versus why so much of this stuff just isn't working - and why we're not putting together properly governed RPA rollout plans like we do with ERP software and SaaS platforms.  Why are we making such a mess with this, when we could have so much to benefit from?

So join us in Chicago this September 19th for FORA the inaugural council meeting that finally debates the true Future of Operations in the Robotic Age

FORA is the very first industry council is established to bring together buyside operations leaders, service providers leaders, expert advisers and technology developers to steer industry’s transition to the Digital OneOffice™.  

FORA’s mission is to bring together the leadership from senior buyside operations leaders, service provider leadership, expert advisers, and technology developers to set the agenda for the transition to the Digital OneOffice™, and to develop an industry mandate for navigating and managing the creative destruction that looms. Supporting the FORA initiative is the IEEE’s Intelligent Process Automation Standards initiative that will encourage further research and investment, leading to powerful and attractive new service offerings. But the commercial frameworks needed to encourage and sustain wider deployment of these technologies are lagging because they fundamentally threaten established models.

In order to communicate the learnings from the FORA meetings, the group will produce a quarterly “FORA Mandate” that communicates core recommendations to the industry from the group meetings that will be held at quarterly HfS Summits.

So how can you get considered for Council Membership?

HfS will consider applications to the FORA Council based on seniority and relevance. Are you interested in participating? Just email us at [email protected]

This is a really important development as we consider the future of services and operations amidst all this creative disruption. I hope to greet many of you personally in Chicago this September.

Cheers,

Posted in: Outsourcing Events

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Stop sawing that plank with a fish: An RPA 101

May 16, 2017 | Ollie O’Donoghue

These days, we talk about Robotic Process Automation as if it’s the remedy to all modern business woes. But, as with all technologies, the capacity for RPA to deliver value has its limits.

Last week I had the privilege of attending an RPA user group event hosted by the Global Sourcing Association packed with service providers, buyers, and experts - where this solutions capacity to deliver was laid bare. After two refreshingly honest presentations by automation gurus from  Symphony Ventures and Thoughtonomy, the roundtable discussions kicked off. Several buyers joined me, alongside two of Symphony Ventures finest consultants, Katharine and Nick, who were both more than willing to impart honest and impartial advice. While the parameters of the conversation were broad, there are four key takeaways that I’d be happy to share with you. I have built all of the following out of the challenges brought to the table by practitioners and buyers. With the answers that came from the knowledge and expertise of the experts or those having weathered some implementations.

 

1. RPA isn’t the salve for all wounds

There’s no doubt about it, the technology is powerful, but it’s important to recognise that there are limits. Environments with chaotic data sets or irrational processes are not suitable without a huge amount of refining. Nor are you likely to find much success if processes rely too heavily on external data sources – unless the owner of the source is particularly liberal with access.

RPA works best on processes that are formulaic and rules-based. If your process has a set input required to achieve the desired outcome, with a series of consistent steps in between it’s in scope. Even if there are a huge number of steps or the rules to follow are relatively complex, a solution can be built, albeit with the hard work and knowledge of providers and experts.

2. Don’t be tempted to go rogue

Some of you may be tempted to leave other areas of the organisation, especially IT, out of an RPA project. However, all the experts in the room warned against doing so. Inviting IT to the party is essential to help navigate through some of the trickier aspects of the implementation with solid business and technical knowledge.

Some of the providers I spoke to at the event provided plenty of examples of when their implementation was made just that little bit harder when relations between the buyer and IT were…less than harmonious. The key is to build relationships with all stakeholders before embarking on the project to ensure your RPA project delivers the most business value and has the greatest chance of success.

3. The process may have RPA written all over it, that doesn’t make it suitable

Let’s say you have a process that ticks all the boxes – boring, formulaic, rules-based stuff that nobody wants to do. Although it seems perfect, it may not be suitable for a simple reason: the ROI isn’t there. Examples abounded of processes pushed forward for consideration that was already relatively inexpensive to handle, making the cost of automation fail to add up. Such as a long-winded rules-based process that, in practice, was only handled by a single person in the first place.

After all the calculations are laid out on the table, the economics of automation may not add up, at least from a cost saving perspective. However, be careful of ruling it out completely as it’s possible that freeing up someone’s time or improving the process may add economic value in another way, by improving customer and employee experience, for example.

4. In some cases, RPA is the last solution on the list

For some processes implementing RPA is the equivalent of hitting a nail with a sledgehammer (I ruined a perfectly good shed attempting that). For others, it’s like sawing a plank of wood with a fish, just plain unnecessary. For example, a process highlighted for consideration due to its resource demands may, in fact, also be managed elsewhere in the organisation. The simple fix would be to merge all parallel processes to not only ensure consistent outcomes but also to reduce the resource overheads significantly.

Halting unnecessary processes or merging duplicate ones may be the solution businesses are looking for instead of automation. Katharine and Nick, the consultants we spoke with advised that they often start an engagement first by taking a holistic view of all processes before jumping in with an RPA implementation to make sure it’s the best solution for the problem.

Summary

RPA simply isn’t the right solution for every problem, and these are just a few of those discussed at the user group. Perhaps it’s the right time for the industry to take a step back and understand what value the technology can add in different situations. Instead of pushing it as the miracle cure for all business woes – a perception facilitated by buyers looking for a shiny new tool and providers seeking to make the most of the RPA Gold Rush.

Bottom Line: Without a doubt, RPA is a powerful technology, but for some business challenges there are far more effective solutions to consider.

Posted in: Robotic Process Automation

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Transforming the Digital Customer Experience—Four Ways to Move from Theory to Practice

May 16, 2017 | Melissa O'Brien

The presentations and interactions at the recent Sitel customer event illuminated a few key themes that customer experience oriented companies can take away as they look to implement customer experience strategies within their organizations and in conjunction with their service providers:

  • Align the entire organization to customer centricity. To effectively serve the digital customer, what we at HfS call operating as OneOffice, the corporate focus needs to create a work culture where individuals are encouraged to spend more time interpreting data, understanding the needs of the front end of the business and ensuring the support functions keep pace with the front office. T-Mobile shared an initiative where people in the organization that traditionally have “nothing to do” with customer experience listen to phone calls with various problems from customers. They found that someone in a back office support function listening to the issues on customer calls helps “make things real” in other parts of the business. Hearing the customer’s experience of a fallout from an order management issue, for example, really helps to illustrate how every function in the company impacts the customer experience—and the business. It also, in turn, helps discussions for how to improve operations from the back to the front office. 
  • Find the right blend of digital and human touch to meet customer expectations. This is not going to start with technology, it’s going to start with understanding your customers, their expectations, and pain points. Companies thinking about digital customer experience need to start mapping the customer journey, which in many cases means using digital technology along with the human touch. Intuit discussed its implementation of “SmartLook” video chat, which has been a successful initiative to better support customer inquiries about their TurboTax product.  Intuit finds itself competing with the in-person tax preparation services, so in order to supply that high-touch experience, the software company set up the capability for one-way video so that the customer can see the representative helping them with tax questions, and also the ability for the rep to draw on the customer’s screen. They quickly found that customers really value the human connection, and scaled from 100 to 4500 live video agents in a matter of months, including special training for being on-camera and shipping out uniforms and blue backdrops for its work-at-home agents.  The results are impressive: decreased call handle time, a resolution rate improvement of 10 points, and an NPS increase of 20 points putting Intuit in the 80s (world class service levels!).  It’s a great example of the blend of digital technology and the human touch that is still very relevant for many customers and types of interactions.  This is not without drawbacks of course—there were many lessons learned about the training involved and implications of having a live agent on screen with customers (i.e. customers taking unflattering screenshots of the agents…).  Finding this balance will always be a work in progress as technology and customer preferences change.
  • Support customer experience by making digital assets universally accessible, and embracing the cloud in a way that enables genuine scalability. As the CMO of Wyndham (a chain that opens two new hotels every day) pointed out, there’s a lot of integration behind the scenes in order to be fast and nimble enough to meet customer expectations.  Two years ago the hotel group did not have high-resolution photos for all of its properties. Digital images were spread across five different content management systems, which didn’t have the space to store them—and in fact, it was often up to the individual properties to manage and store these images. Wyndham decided to make the digital team part of the CMO organization, and using several partners, shot a million high-resolution photos in the last 18 months and consolidated them on to one cloud-based content management system.  Adding these photos to its websites and mobile apps has already generated a 40% conversion increase, a 52% mobile bookings increase and a 10% of return visitors.  The next steps in Wyndham’s transformation journey will be to use all of these images along with customer data to create better, personalized experiences online, and the company needed this streamlining to get to the next step in their digital transformation. 
  • Embrace design thinking as an ongoing method to promote customer centricity and design frictionless customer experience. CapitalOne described its desire and journey toward becoming a tech company first and a bank second. Because of the threat from the growth of fintech companies, the bank has altered its core business strategy, impacting who they hire and how they operate.  One major change has been the use of design thinking as a way of learning. They use the term “customer back”—meaning always start with the customer and work your way back.  As this has culturally taken hold at CapitalOne, the bank has found that it is not just for people with design in their title, it’s being embraced across the organization.  Results from these efforts have included customer-focused changes which remove barriers and make the customer experience more intuitive, such as ways that customers can pay their bill. For example, customers can now use Echo to ask Alexa what their balance is and pay a bill. CapitalOne has also implemented a chatbot named Eno who is available on SMS—customers can pay bills, get their balance and other basic functions.  By listening to customer feedback, they’ve also implemented the ability to “unfreeze” a card that’s been flagged for fraud for just 15 minutes through their mobile app—for the busy customer that just needs to make a transaction while on the go.   Involving customers in the design process has increased their ability to serve customers in the ways they prefer.  It’s important that design thinking continues as an ongoing effort, as markets evolve and business needs change. 

As each industry is being disrupted in new and different ways, it’s important for every organization to start somewhere – take these lessons and embrace small and quick wins in order to move forward in becoming more customer-centric organizations. 

Posted in: Customer Experience Management

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A Moment of Transformation with the “New Sitel”

May 16, 2017 | Melissa O'Brien

Acticall Sitel Group is undergoing a “moment of transformation,” as they put it – “pivoting from a contact center to a group of global services, innovative and socially engaged, dedicated to providing exceptional customer experiences.”  What this really means in a world overflowing with overhyped CX buzzwords isn’t easy to tell, and here’s what I learned as one of the analyst community members that spent time with Sitel executives and 70+ clients and prospects at its 2017 Miami Analyst Day and corresponding Customer Summit this week: that a company in transformation needs a North Star – one that is bright and shiny to illuminate the path forward. Acticall Sitel has a lot of stars, but it’s not yet clear which one will stand out to lead the way.

 

Diversification: The Ventures Ecosystem

The “New Sitel” is the portfolio of companies: the traditional Sitel contact center business and a number of other “venture” companies brought on with Sitel’s acquisition by French based Acticall Group in 2015.  This new Sitel has been a couple of years in the making, but the story that is emerging is an interesting and compelling one to buyers of contact center services and those of us who are enthusiasts of the contact center being a core element of customer experience design.  A few highlights from the event:

  • The Social Client, one of the ventures, is a customer experience consulting and strategy company focused on implementing design elements like visual IVR, employing design thinking and journey mapping.
  • The Learning Tribe, a training and learning entity focused on digital aspects of learning, i.e. mobile and social learning, brings gamification and certification elements to training environments in need of transformation. As the head of training for a major corporate bank said, “we need to be digital internally within our organization as well as externally with customers.”
  • The Premium Tech Support venture is providing white glove services to clients and generating revenues through cross-sell and upsell opportunities while utilizing the Customer Insights analytics venture to optimize its services using predictive customer analytics. 

The big picture of the new Sitel still seems a work in progress, especially in terms of commercial engagements, as the service provider retrains its sales staff and restructures incentives to more effectively sell across the ecosystem—but the passion and vision is certainly present. And Sitel is also investing in AI with a quality monitoring tool, empowering a trend the provider calls “botshore,” the use of bots as a lever along with offshore and nearshore options-- a concept which jives well with HfS’ vision of using increasingly intelligent automation as just one of the levers to pull when it comes to engagements with service providers. 

Pivoting the ventures toward American business will be a challenge, but very recent leadership additions, including a creative agency veteran in the role leading The Social Client and a BPO sales mogul in place leading sales in the Americas will bolster the potential for execution across the organization.  Sitel will need to continue to think through the messaging and branding of these ventures: What truly represents the capability and value of each one and as part of the whole new business? For example, the name “The Social Client” is limiting and not representative of its capabilities. Sitel seems to be sitting on a gold mine and needs to unearth the potential to let it shine.

The Bottom Line:  The time is ripe for a legacy call center provider to really transition to a customer experience design leader

In this world of “digital transformation”, many enterprise buyers are asking the question, who do we go to for design?  Instead of paying boatloads of money to a traditional consulting firm, can they leverage their trusted contact center service providers who already know their customer inside AND out, and are investing in capabilities?  I think the opportunity is there.  We have been talking about it for years, but have yet to see a pure play contact center BPO provider really cultivate and hone a brand for the customer experience design element.

One of the elements that has consistently made Sitel’s events relevant and useful in the past (even pre-Acticall) is their transparency and willingness to give accessibility to their clients—especially at an event like this one, where we had the opportunity to meet with customer experience leaders from many industries and with various goals.  The customer presentations were extremely valuable in understanding these enterprises’ mindsets and they were clearly getting a lot of value from each others’ stories as well. It’s quite a network that Sitel is establishing here. 

What we now need to see from Sitel and its peers is real life examples of using the “value-added” services” – including digital marketing and customer experience design- which are presently a tiny percentage of revenues for Sitel and other contact center companies.  On the same note, buyers who are constantly screaming “bring us innovation!” need to get involved and work with their service providers about the opportunity engage in these services.  As soon as we start seeing more case studies and success stories of turning this theory into practice, the doors will open wide for those providers and buyers willing to invest and take the risk to really transform.

 

Posted in: Customer Experience Management

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WannaCry emphasises the dire need for automation and cognitive in security

May 16, 2017 | Christine Ferrusi Ross

This is me jumping on the bandwagon with an opinion about the global WannaCry ransomware attack last Friday. As of my writing this, this attack hit over 200,000 companies, hospitals, universities, and other groups in more than 150 countries according to Europol. It’s been headline news.[1]

While bandwagon jumping generally has a bad connotation (doing or supporting something just because it’s hot at the moment,) security is one of the bandwagons you should proactively jump on. Right now. Really.

Security tools, services, articles, etc. are all popular because security attacks are popular – and increasing. So yes, if in the past you thought your passive following of whatever standards were placed in front of you was good enough, you need to break out of that rut and get proactive. Too often, standards aren’t keeping up with the changing threat landscape. You need to constantly search for new security tools, skills, and services to help you protect your firm, your employees, and your customers to achieve digital trust in the market.

In fact, the recent attack only brings findings from HfS’ recent Managed Security Services Blueprint into clearer perspective. We heard from both providers and security executives that effective security programs shared key characteristics:

  • Automation everywhere possible. There are too many threats and attempts for your security team to monitor them without automation – you’ll never collect the necessary data manually. Your automation investments need to include appropriate analytics to evaluate and find patterns in the data so your team can take appropriate next steps.
  • Investment in cognitive computing. Predictive analytics and cognitive computing investments for tomorrow aren’t negotiable. Today’s environments can collect and analyze, but you also need to be focused on systems that learn from current data to build predictive models and help you prevent attacks, not just respond to attacks as they happen.
  • Focus on employees and the human element. This takes two tracks: 1) Educate employees more often and more consistently about phishing and other techniques that attackers can use to get credentials and other sensitive information from workers to attack company systems. And 2) keep your security team’s skills up to date. The talent shortage in security is exacerbated by the skills gap – staying current on all security trends is daunting but necessary. And security teams are so overwhelmed already that it may seem they don’t have time for training. It’s time to evaluate your hiring and training for security to look for ways to bring in non-traditional talent and get them up to speed faster to ensure you’re protected.

Bottom Line: Treat security as your business, not as an enabler

Without effective security your business won’t survive – either your company systems will be brought down, or more likely, customers won’t want to do business with you if they see you as a threat to their own information security. The WannaCry ransomware attacks is another proof point that security threats are increasing in number, scope, and scale. Jump on the security bandwagon and follow practices of leading edge security practioners for effective programs.

 

[1] A few of the news stories include:

https://www.nytimes.com/2017/05/12/world/europe/uk-national-health-service-cyberattack.html

http://www.bbc.com/news/technology-39924318

https://www.cnet.com/news/watch-wannacry-attack-geography-in-real-time/

Posted in: Security and Risk

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Frank D'Souza: We're now experiencing the biggest shift since the Internet

May 12, 2017 | Phil Fersht

 

It's always more fun to be the disruptor than the disrupted in markets where innovation is the key differentiator and commoditization the curse. The world of technology is a constant challenge as programming languages become commonplace, processes increasingly standardized and automated, and global service delivery efficiency a bread-and-butter offering. How can you continue to grow at a double-digit clip, while maintaining profit margins of 20%+ amidst cut-throat competition and clients forever eager to batter down their costs?  

Fortunately, the entire role technology plays is changing at a pace that is faster than most industries that can barely tolerate, which keeps driving new opportunities for smart firms with a disruptive appetite at their core and a willingness to live outside of their comfort zones. Today, enterprises are asking for business problems to be addressed and simply expect their service partners to get the job done. It's no longer "Provide me with 50 developers for this amount of time to perform these tasks", it's more, "We need to redefine our healthcare insurance business to be more competitive in the market to survive - come help us do that", or "These new banking regulations are crippling our ability to remain viable - what can we do to get ahead of these and operate effectively in this environment, faster than our competitors?"

Hence, it's up to the ambitious service providers to pivot how they address their clients' needs by redesigning business operations through smarter automation, process design and a much more proficient understanding and orchestration of their critical data sets. This is what digital is really all about - and this is where Cognizant CEO, Francisco "Frank" D'Souza is determinedly taking his organization. Cognizant has been Wall Street's golden child of IT services growth over the past decade, the firm ballooning from $2bn in 2007 to $13.5bn exactly a decade later, and last week announced 11% year-on-year revenue growth and a 26% increase in year-on-year net profits to $557m. Cognizant continues to outperform the market with relentless growth and appears to be on a new upward growth trajectory after a challenging 2016, which saw the whole IT services industry tackle this new secular shift, which Frank believes if the most pivotal transition since the onset of the Internet itself.

I caught up with Frank this week in London to get a little deeper into this pivotal industry shift and learn more about how he intends to keep disrupting his market.

Phil Fersht, CEO and Chief Analyst, HfS Research: Frank – great to see you again. Was good for the whole industry to see you guys announce strong results last week – is the gloomy cloud that’s been hovering over our industry lifting, from Cognizant’s vantage point?

Francisco D'Souza, CEO Cognizant: Phil, last year was an important foundational year in our pivot to digital. I think we were ahead on some of the digital thinking, code halos and SMAC (social, media, analytics and cloud), we have been talking about those for many years. I think last year was the year that picture, at least in our minds, and our clients’ minds, crystallized around what are the specific opportunities around digital. Prior to last year, digital was the typical catch-all term used for lots of different things.

I think it’s become very clear, Phil, with every day that goes by, is the notion that if you think about a company’s enterprise model (what is the business model, what’s the operating model and what’s the technology model) it’s now become clear what is the implication of digital technology at each layer in that stack and by industry. What does that mean for financial services, what does that mean for healthcare, what does it mean for insurance?

Last year was about crystallizing around that – we reorganised the business we took all our capabilities, we grouped them into three big practice areas: digital business, digital operations, digital systems and technology. Within that we really focused and emphasized the key digital themes and trends in each of those areas. If you think about the technology space we built and emphasized the cyber security aspects, we built and emphasized performance and scalability,

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Posted in: Digital TransformationIT Outsourcing / IT ServicesOutsourcing Heros

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Are automation PoCs leaving you in robotic limbo?

May 09, 2017 | Reetika Joshi

Whether its cognitive automation or RPA tools they’re trying to implement, a large percentage of services buyers are stuck in a sort of robotic limbo. As we launched our new automation council “FORA” at HfS, Phil brought up a huge challenge, “Why aren't those [anticipated] 40% cost savings happening each time someone slams in some software and hopes it somehow eliminates manual labor because they can access a bot library? In fact, why are a third of RPA pilots just left hanging with no result?” 

Why are PoCs entering robotic “limbo” or failing, and what is working out there?

Here’s what I heard from two automation practitioners in large financial services organizations:   

PoCs that don’t begin with the right kind of buy-in have a longer time to value

The VP at a financial services company considered using Watson technology to help their sales force be better informed when first interacting with potential customers. They designed a PoC that would allow a sales person to ask questions like, “Who are this customer’s competitors?” Watson could take this natural language query and apply it to the company’s own and external data sets and come back with a synopsis of facts to make it easy to identify trends. However, after the PoC, it became apparent that various stakeholders like the operational heads of the lines of business didn’t understand the breadth or relevance of the technology. Was Watson overkill for their needs? After the PoC ran, these executives asked, “Isn’t this what Google does? Why do you need to invest in this solution?”

With the Head of Sales behind the project, the organization found it easy enough to get started but then got waylaid on the way to the finish line. The team had to backtrack to explain how the fundamental cognitive technology can help achieve more meaningful and timely answers to the questions the sales team could ask. The stakeholders didn’t understand the difference that data mining could bring – versus manual searches for each company or trend. The solution would bring more relevant and actionable data to sales teams that could impact closure rates and revenues. After a rather lengthy “limbo” in educating all parties, the VP involved the top performing account managers and used their ideas to design the front-end user interface. This helped the team build a relevant solution that leverages the capabilities of Watson and build internal acceptability, which accelerated the path to live deployment. The team is now expanding its user base and exploring ways to leverage more Watson APIs in the solution.

PoCs could get dismissed as hypothetical technology proofs with no grounding in reality

Peter Quinn, Managing Director of Automation at SEI Investments Co. started the RPA journey in their organization’s securities processing function late last year. He took a position not to do PoCs, feeling that they are too easy for skeptics to shoot down, and only prove hypothetical scenarios while exhausting time and resources. Instead, his team decided to run production pilots, a hybrid of PoCs, pilots, and production phases. With this format, the solution is designed with more rigor than a PoC, and is deployed in a live production environment with real transactions taking place.

Peter stresses the importance of demonstrating to the larger organization the efficacy and effectiveness of the bots deployed since they are working in a live environment. He shares, “I wanted to do things that weren’t trivial, like RPA tools that just gather information and create reports. When those processes work with 98% accuracy, that could be considered as acceptable. But when they are moving client securities or money, no margin of error is acceptable. We are running functions that are core to the financial operations of the bank rather than something that’s low in criticality. When they work, the results speak for themselves – we are seeing greater accuracy from the lack of manual errors.” The implementation challenges that this team faced with the production pilots were related to other aspects of their technology landscape that needed to be fixed, such as conflicts with how the environments were configured. It could have gotten “stuck in limbo” because to really build automation as part of the core processing backbone, they had to work through a lot of unanticipated factors. It didn’t however because they had relevant business and technical stakeholders involved and a general spirit of collaboration. SEI is now armed with “real-life proof” and is undertaking several more process automation.

Testing and sharing as you go help ensure you are solving the right problem and updating it as needed, as well as adjusting the technology solution.

What is common in these practitioner experiences is the importance of building stakeholder buy-in. You need to have them involved in defining what problem to solve as well as testing the solution and being ready to make quick adjustments to address what else in the infrastructure or environment is impacted as RPA is rolled out.  The problem you are trying to solve, the complexity, and the level of stakeholder involvement are all necessary factors to consider. It can influence the type of approach you take and help identify the issues you need to tackle upfront before even getting started with automation tools, as well as adjust quickly along the way.

The Bottomline: Don’t feel obligated to jump into automation PoCs only to be left in limbo down the road. Iron out the ‘whats’ and the ‘whys’ before getting into the ‘hows’.

There’s more than one way to kick-start your intelligent automation journey. Find the one that works for your organization’s culture and political structure—do you need to educate or provide examples or both?

Posted in: Robotic Process Automation

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Automation doesn’t have to be a dirty word…

May 08, 2017 | Ollie O’Donoghue

Without a doubt, the impact of automation on the IT Services industry is a topic of much debate and contention. The challenge is that speculation drives much of the discussion, rather than quality data and analysis.

While the subject of automation has been discussed a few times on the blog, I feel compelled to add my experiences and those of the IT professionals I met on my travels to the discussion.

Not long before joining HfS, I spent several months presenting research on automation at events and conferences across the UK. While the research covered a broad range of topics, automation in IT services was by far the most popular. After a few presentations discussing the increased adoption of automation and the growing capability of the tooling, it became apparent where the popularity of the topic originated - fear. After each session, a small gathering of IT professionals would question me on job security, headcount decreases and how automation augered a bleak future for the industry.

It’s not difficult to see why the audience felt this way. The mainstream media and even some analyst firms have been stoking the climate of fear with considerable vigor.

So I went back to the drawing board and changed my presentation. I took a fresh look at the data to examine what was happening in the industry – did we genuinely need to worry? Beginning with an impactful quote most media outlets were running with – something along the lines of “be terrified, the robots are coming” – I started to dismantle these theories with my research data on employment trends, headcount increases, and industry perception.

While many argued that automation would lead to job cuts, my data showed the opposite. Organizations recognized the importance of technology to their businesses and were investing in the services needed to support it. The data revealed that in organizations with higher levels of automation, workers were not disappearing, they were moving to higher value areas of the support structure - taking on strategic projects or developing services.

At the end of the presentation, I concluded that the reality of automation’s impact on modern IT services was far from the bleak picture painted by other analysts and consultants.

Nevertheless, a few minutes after the session ended the same horror stories started to emerge: IT leaders facing a backlash from staff as automation projects ramp up and professionals working themselves into a frenzy over their job security if projects continued. It was frightening stuff.

Crucially, my research revealed that the cause of this panic doesn’t come directly from the automation itself – there were almost no real-life examples of automation leading to sweeping changes in any of the organizations I was working with. Without a doubt, much of the fear was generated by analysts and media outlets whipping up this distorted perception, but surely there must have been another force at work.

After a bit of digging around the real cause of the hysteria became clear. In organizations with little or no perception issues, it was clear that the leadership team had taken the time to communicate with their teams. Conversely, those with stressed and worried staff had not.

When I questioned an executive who sought advice on soothing fears in his team if he had clearly explained his vision, and what the outcome of the project would be, he replied that it was obvious what he was trying to achieve. If that were true, the perception crisis in his organization would not be there.

Successful automation projects have an engaged team working behind them. The most effective I have seen understand what will be automated and why. They know what impact it will have and, for the most part, agree it was an area of manual work they found repetitive, boring and unfulfilling anyway. They eagerly anticipated a time when they could dedicate their efforts to more meaningful and valuable work.

Under different circumstances, this committed group would be dealing with the same fear and stress as their peers in organizations with less effective communication.

In the noisy information age we now live in, it’s easy to get caught up in the hype. Business leaders have an obligation to provide clear, effective communication that outlines the vision and journey of automation projects. Without the context and understanding they provide, an engaged team can quickly turn into a stressed one. And a stressed team will undoubtedly hold your project back. It’s not hard to understand why an individual afraid of becoming obsolete may not be working towards your goals with total enthusiasm.

Bottom Line: Effective communication strengthens the fine line between a successful automation project and one held back by a nervous and stressed team.

Posted in: Robotic Process Automation

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Don’t let our crazy orthogonal ideas be pecked to death by negativity

May 08, 2017 | Jamie Snowdon

A few weeks ago, I was fortunate enough to spend some time talking with the head of IT of a large transportation company – and we talked about the future of his job and the most important things impacting his role. When I asked him what was the main issue getting in the way of him adding value to his business, he said it was a cloying inertia brought about by a thick soup of negative thinking.

The number of people in his organization that focus on the way things have been done in the past and the reasons why things can’t change, were a source of incredible frustration to him. Incremental change was possible, colleagues understand how processes evolve, so innovation could be staged, but it was very hard to implement anything totally new. We joked that original thinking was being pecked to death by negativity, like a flock of miserable seagulls.

As an analyst, this is something really close to my heart – if we are to produce anything that approaches original thinking, we need an environment where ideas are cherished and even the craziest thought is welcome – although it will ultimately need to stand up to scrutiny, the original thought can’t be wrong. It’s only when you make cerebral room to nurture some crazy, orthogonal thinking do you create inspirational work like the Digital OneOffice.

So what needs to happen, how can this change? How can we get people to take leaps of thought rather than increments?

Phil’s recent blog “Is your current job the end of the line?” delivered seven action points directly to the chief “peckers” of the world. Distilling that, the most important thing organizations can do to encourage this behaviour and become more open is to move away from traditional hierarchical relationships, look at the idea itself and any data that supports the idea. It is the addition of data and more evidence that helps to shift thinking from more traditional decision making.

It’s interesting that the message, at least in terms of its overall importance, seems to be getting out at last. In a recent survey of 300 major Global 2000 enterprises, we asked IT leaders about the importance of some c-suite directives to their IT strategy.

This graphic shows that IT decision makers realise the best way that they can increase the relevance of IT within the organization is by supporting more predictive decision making. This is a crucial change in mindset, taking IT away from its most recent manifestation which has almost been as a custodian of IT, or a gatekeeper, focused on reigning IT in and keeping the costs down.

Bottom Line – data gives crazy thoughts wings

We suspect that part of the embracing of data by IT departments goes back to my friend and his battle with the naysayers. Data levels the playing field and gives more people a voice. It gives more power to the elbow of anyone seeking to make a change. An IT department that delivers insight will be listened to, as opposed to being largely ignored as a legacy function tasked with keeping the lights on. Let’s stopped being pecked to death.

Posted in: IT Outsourcing / IT ServicesGlobal Workforce and Talent

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Is your current job the end of the line?

May 06, 2017 | Phil Fersht

 

A new trend is developing in the tech and business world and the speed at which it is happening is alarming. The need for people is waning as companies seek to scale themselves profitably on a digital backbone - and it's having a serious impact on our career paths.

When companies historically did layoffs, it was because they were in financial peril and had no choice but to saw off costs to stay solvent on the balance sheet. It was always painful, because you needed people to grow your business. Sacking people was not a good thing to do.

Suddenly it’s in vogue to shed people

However, if you were unfortunate enough to get caught in a layoff, you dusted off your CV, went out on the job market and (usually) found yourself something pretty quickly. Companies needed people – whether they were superstars, or solid foot soldiers; when you needed an employer, you would always find something.

Now something different is happening in the mindsets of business leaders – companies which are doing really well are in the process of proactively removing staff – both at junior and senior levels. You really don't want to get caught up in one of today's layoffs if you're eager to stay in a similar job in future, because the modern business is adopting a new mentality - cut costs and scale profitably with a digital backbone.  Adding armies of people is no longer the order of the day when you peer into an uncertain future, and many savvy businesses are eagerly looking to

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Posted in: Cognitive ComputingRobotic Process AutomationGlobal Workforce and Talent

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How a chicken, Clay Christensen, Nikki Beach and a bunch of Utility executives provide a sunny outlook

May 05, 2017 | Derk ErbéBram Weerts

This week we crossed the Atlantic to meet the cream of the crop of the utility industry in Miami for the International Utilities and Energy Conference, hosted by Accenture. A packed agenda entertained the brightest minds in the utility space from around the globe.

 

We were in for a surprise: from the first session to the closing key-note it was one big future-oriented gig, focusing on business value instead of enabling technology. No sales pitches from the provider (many providers can learn from this), zero bad jokes... and a highly engaged audience (yes, we are still talking about utility executives here) that wanted to smell, touch and work towards a better future with more and better client interaction. They all want to be more profitable but more important (for real) greener! Their customers demand it; the infrastructure is ripe for an upgrade, and so the question is, why not make it happen?

Fossil is the new uncool, and renewable energy (with loads of digital components for their clients) the new hipsters, the future of utilities!

Let us explain with a couple of fantastic examples that had a high impact on your peers at this week's event. Over to you Derk!

Thanks, Bram. We had an interesting time for sure. Let me give you some quick pointers on the new, the unexpected and the future that headlined IUEC 2017.

A dizzying barrage of industry shattering disruptions thrown at attendants

As one Utility executive put it; the first day of the event was a succession of shock and awe, fear and nausea. Florida Power & Light CEO Eric Silagy set the stage immediately; the unstoppable force of renewables and how being clean is good business. It is a vision that not everyone dares to execute on as radically as Florida Power & Light, but they are doing it without hesitation. CEO Silagy provided an excellent example of lowering his customer's bills by taking the most polluting oil and coal plants offline.  

 

In this picture, you see a perfectly well-operating oil based power facility Florida Power & Light just blew up (after many people try to stop them) to build a far cleaner and more profitable (not only for them but also their clients) and this is just one of many examples. Don't wait, just do it. There are always excuses, but just doing it will pay off in the end.

Further, he explained his strategy for relationship building with the regulators, being proactive and ahead of the curve and highlighted Florida Power & Light’s investments to build a more resilient infrastructure to deal with (the ever increasing) hurricanes’ ravaging effects in his service area.

Salim Ismail of ExO Works and Singularity University, talked about Exponential Organizations, and the drastic competitive forces these present in many markets. As electricity shifts from a scarce resource to an abundant resource, the dynamic of the market changes. Exponential organizations find business models to leverage abundance. Ismail explored Airbnb, GE and Ford’s journeys. One key takeaway that resonated with the audience is how innovation in large organizations is almost impossible. Innovation needs to be positioned at the edge, insulated from the internal organization. Large organizations have immune systems that attack any threats to the status quo, i.e. innovation. This is particularly relevant to utilities; being large, engineering-oriented and traditionally conservative organizations.

Accenture’s Digital guru Mark Sherwin brought his analogue chicken Penny to illustrate digital business models (his chickens and eggs turn out to be some of the world’s most expensive when factoring in the services he gets offered through digital channels to make his and the chicken’s life easier, from predictive food delivery to chicken hotels).

MIT professor George Westermann implored the audience to challenge pre-digital assumptions, as those hamper real transformation, reinforce the status quo and limit the ability to think outside the current frame of reference. Unintentionally providing great input for Design Thinking exercises.

Accenture’s Chief Strategy Officer Omar Abbosh shed light on disruptive forces over the last decades, from mainframes to IoT, AI, and Quantum Computing. He provided a great comparison of how he and Accenture’s leadership reinvented the strategy five years ago to rotate to “the new,” completely overhauling the organizational structure to change the culture, and how utilities are on a similar trajectory.

Vlogger and, more importantly, former monk Jay Shetty reflected on the Millennial mind, demystifying and busting myths. It turns out; millennials are not as scary as you might think. Jay called on the audience to incorporate four ‘Millennial mindsets’ (which are great for anyone by the way): the leadership of a coach, the fresh eyes of a child, community thinking and the mindset of a coder.

Missy Cummings, one of the first ever female US Navy’s fighter pilots and currently Duke professor of the Humans and Autonomy Laboratory Duke Robotics, talked about the highly relevant topic of drones and other unmanned vehicles and robotics’ potential in the utility industry. One of the key points she made addressing the fear robots will destroy jobs, is robotics and automation will likely create more jobs than destroying them, albeit different jobs requiring different skills, providing examples of people and robots working side by side in aviation.

It was time to evaluate all this and time to hit the Miami’s South Beach and more specifically Nikki Beach. The first feedback trickled in, and people had a lot to think about. Clearly, the platform that is IUEC worked.

Day two focused on more practical, “how to” examples and some great new research findings from Accenture and Bloomberg New Energy Finance about the industrialization of renewables, and Accenture’s global lead for Smart Grids Stephanie Jamison presented fascinating findings from a study of distributed generation (DG), focusing on business disruption of DG and the lack of clear forecasts utilities have around the impact of DG integration.

What stood out

At previous editions of IUEC, there were still reservations amongst executives about how fast digital and renewable energy would force change upon them. Those reservations are completely gone. Overall, utility executives have a positive outlook. Solid examples and cases are providing proof points and inspire the way forward, but there still a lot of work to be done.

A terrific event was wrapped up by living legend Clay Christensen, the godfather of disruptive innovation and Silicon Valley’s favorite guru. He gave the audience an excellent perspective and frame of reference of disruptive innovation and clues to shift capital investments to disruptive innovations to prevent becoming the next Blockbuster.

The Bottom Line

It is all about disruption and making a play instead of being played. Harvard Business School professor Christensen expressed his desperation for his industry - higher education - being disrupted with lightning speed by online learning and corporate universities. He did not worry too much about Harvard itself, but many universities are not that well funded and will be disrupted by new forms of learning leveraging technology. His response, without any hesitation, to a question about disruption in the utility industry was: “If you all pray for me, I will pray for you.”

From Derk and Bram; Godspeed, safe travels back home and until next time.

Posted in: Energy

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“Igniting Innovation”: KPMG features an experiential approach to digital transformation in its Analyst Day

May 05, 2017 | Christine Ferrusi RossBarbra McGannMelissa O'Brien

Just about 90% of CEOs who participated in a KPMG survey are concerned with the issue of changing customer loyalty, and the majority believe current their company’s products and services won’t be relevant to current customers in 3 years. That means they need innovation – now. They see technology (often referred to as “digital”) as an opportunity to move, but 85% of the surveyed CEOs feel they don’t have time to think about disruption and how to respond to it with innovation. This sets the scene for KPMG’s Analyst day recently in Boston. KPMG looks to bring purpose and passion for helping clients be successful in making innovation a part of the core of their businesses – through a diverse workforce, solutions, and collaboration.

With this backdrop, four themes stood out to us during the day about how KPMG is working with its clients:

  1. A vision for “OneOffice” – work designed to address customer needs using “digital labor” and systems. Digital transformation is (finally) moving from the front office (customer touchpoints) to include the middle and back office (business functions and transactions) – and talk is moving from “how do we use ‘digital’” to “what problem do we want to solve for our customers and how do we use the possibilities of talent and technology to do it.” At HfS, we refer to this concept as “OneOfficeTM” – the need for businesses to break down silos in their organizations to create a more effective data and workflow for business outcomes, so this theme resonated with us.

As we are focused on “ making it real” and providing examples of where it is happening, we appreciated the story that KPMG told about a client they worked with to map out the customer experience. They registered a number of customers on an app and these customers recorded their experience in real-time, as did employees. KPMG captured the data in the Pathfinder tool and used it as input during a journey mapping session with employees from across the organization, front and back office, including a finance director, a customer service manager, and a valet. They talked through the points in time when the customers and employees had a poor experience and came up with ideas that were then prioritized for addressing through the client’s own innovation management approach. What stands out here is the breadth of people included in capturing the experience (customers and employees from different business units and IT) and the way the experience was captured (an app in real-time), which led to in-person workshops to map out various customer journeys and an action plan.

 Additionally, staying true to the “ embedding innovation” theme, KPMG trained a number of the employees in departments throughout the client on the design thinking principles and methods used in the initiative. These people are networked as a COE. The team also has access to an analytics tool to continue to capture and analyze data on their journey.

2. A focus on defining and enabling the evolving role of workers and work. “Even in a digital world, humans are still the most important investment, the secret element of our brands, and the magic asset in the company,” said Robert Bolton, capturing the tone of the recent day. One example of a workforce transformation in progress was launched when a client started a discussion about the size and shape of the workforce of the future. This has led to questions such as “How do you know you have the right size?” “How does it have to change because of the advent of RPA and artificial intelligence?” “What are the impact on entry level jobs and the way those jobs provide a launching pad for careers?” “How does it impact learning, training, career paths?”

KPMG is not just working with clients to address these questions but shared its own experience in a changing workforce through the use of digital labor. For example, instead of having new hires who are eager, smart MBAs do mundane and repetitive audit work while they “pay their dues,” KPMG is able to automate much of that work and provide a more stimulating and challenging role for the talent they’re bringing on board.  It’s changing the culture and employee work allocation models.

This area of “ digital labor” is one that the shared services and outsourcing group at KPMG is hearing a lot of questions about as well, according to the group’s global head, Dave Brown. Digital labor and cognitive are on the forefront of activity in evolving operating models and defining who (or what) does what. “Digital labor, simply put, is another form of outsourcing,” said Dave Brown.

4. Innovation starts with culture. Innovation needs to be a way of working in companies – it can’t just be siloed in one department or area. Key features of a culture that embrace innovation include diversity – of workforce and partner ecosystem; collaboration; and experimentation (these are also principles of design thinking). Having a culture and environment where it’s “OK to fail” is also a lynchpin of innovation.  To provide a “space” and showcase for innovation, KPMG has broken ground for a new facility in Orlando to provide its clients and train its workforce with a multidisciplinary, hands-on, collaborative, high-tech experiential approach. And it’s partnering with the academic community to help develop (via technology, data sets, and case studies) the future workforce during the university years – for example, combining soft skills like teaming, collaboration, and critical thinking with critical technology skills for analytics and the subject matter expertise of accounting.

5. Deep investments in software to improve and automate complex processes. KPMG’s Spectrum unit created several “business intelligence engines” to automate and analyze several complex corporate processes like third party risk, contracts, and regulatory compliance like Automatic Exchange of Information (AEOI.) Beyond Spectrum, other tools KPMG discussed at the event include its KPMG Digital Responder, for security threat discovery and analysis and its KPMG FIRE regulatory reporting automation tool. While the KPMG teams mentioned a number of tools and IP throughout the day, and showcased a handful, a little of it felt “mysterious” – they were referenced by name and not explained or shown. These days when everyone is still exploring what digital really can do for them, showcasing case studies and tools can be really impactful in getting the message across.

What does this mean to you?

Digital transformation and innovation continue to dominate corporate boardrooms as buzzwords. But actually implementing requires a lot of complex detailed decisions that spur significant changes to the ways companies operate every day. What’s impressive about KPMG’s message is the firm’s ability to talk at the 100,000-foot strategy level but then dig into the last mile delivery details.

For clients that already work with KPMG, if you’re not seeing the kinds of messages the firm presented at the analyst day, then it’s time for a meeting with your account team. Talk about how some of KPMG’s new (and even not so new) techniques are being or could be, applied to your engagement. Don’t take it for granted that your account team will automatically propose new ideas so be proactive in asking for innovation.

For non-clients, take a look at Spectrum and other KPMG tools as stand-alone solutions. The Spectrum team told us they do sell the tools separately – they don’t just get embedded into larger services deals. This gives you the opportunity to get access to KPMG IP and operational expertise without having to exit any existing services engagements you have in place.

For an organization that candidly admits it was on the slower end of developing a stake in front office, its recent investments and acquisitions (a whopping 51 in the last 3 years) show that it’s quickly catching up, and also tying together the concepts of front, middle and back office nicely and in a forward-thinking way.  Using their own interpretation of OneOffice, KPMG is forging ahead to help clients (and itself) break down the legacy barriers to become more intelligent and responsive client-centric enterprises.

Posted in: Digital TransformationDigital OneOffice

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