I am proud to announce we’ve unveiled a very exciting analyst talent to lead our global research team, based in Chicago US, as our Chief Strategy Officer (see bio).
Saurabh Gupta worked with me at Everest over ten years ago where I helped train him up to help lead the firm’s BPO research team. After a distinguished career at Everest, where he earned a very strong reputation as a highly focused and respected analyst in the areas of BPO, banking, F&A, procurement, analytics and the underlying technology platforms, he went onto the buyside with AbbVie (the spin off shared services for Abbott Labs), where he helped craft the firm’s BPO and shared services strategy, working across various service lines and service provider relationships. He then had a spell with Genpact, where he has been instrumental helping them devise and shape the firm’s CFO service offerings and digital strategy.
Saurabh has long eyed a return to the analyst fold and coming onboard HfS is the ultimate challenge for him, where he’ll be leading our global research team and working with all of us to write about real buyer experiences and mapping where enterprises are on their Digital OneOffice journeys, how fast they need to move and what is preventing them getting to their ideal states. I caught up with Saurabh this week to share more with you all what you can expect…
Phil Fersht, CEO and Chief Analyst, HfS Research: Saurabh – it’s just terrific to be working with you again after a decade since we were at Everest together! What took you back to the research industry after your recent years on the buyer and supplier side of services life?
Saurabh Gupta, Chief Strategy Officer, HfS Research: Thanks Phil. I am thrilled to be here. I am passionate about business research and being an analyst was the best thing that happened to me. However, I did want to experience and appreciate the perspectives of different stakeholders in our industry. So after Everest Group, I spent time with AbbVie helping shape their business process services strategy as well as Genpact as their strategy leader for CFO and transformation services. I think…or I hope that getting into the shoes of a buyer and a vendor helps me become a better analyst. Plus, this is an exciting time to be a researcher in our industry. On one hand, we live in this VUCA environment and on the other, we have finally unearthed the next big value creation levers after offshoring in Robotics, AI, and blockchain. So I feel the role of an analyst is extremely important in today’s world.
Phil: So why did you choose HfS? I think we were just a little bootstrapped operation when you were last in the analyst biz….
Saurabh: Where else? HfS has turned the analyst world upside down with its thought provoking, leading edge and futuristic research. With the pace of innovation and change, all stakeholders (buyers, suppliers, tech providers, investors) need to make important bets and decisions about their future. I’ve seen this first hand in my last two roles. And they cannot just rely on past data and trends to make those calls. HfS is the only analyst firm that I know who can help clients with “what is going to happen” versus “what happened in the past”… so this decision was a no-brainer for me.
Phil: Where is the industry right now, Saurabh? Do you see us in a transition state, or is something else bubbling to wake us all up?
Saurabh: As I mentioned earlier, this is an exciting time for our industry…perhaps the most interesting time in my career. It has reached an inflexion point after very long time where it is about to jump a S-curve. The offshore-led value proposition has dominated our industry over the last 15 years. RPA and AI is finally adding a new value lever that can make a difference and turn the game on its head. At the same time, we also have guard against the hype and be realistic in our expectations. We (and that includes analysts, advisors, buyers, and suppliers) also must learn to unlearn. And then watch out for blockchain and distributed ledger….while everything that we just talked about is about shrinking the pie, blockchain promises to remove the pie altogether…can you imagine what will happen if we don’t need system of records after all?
But the even more interesting thing to solve is the puzzle on talent. If I can ever get to influence my daughter, I will be pushing her towards humanities (arts, communications, psychology, creativity) and problem-solving versus left-brain stuff. I think that’s the future!
Phil: So what can we expect to see from you at HfS… what are your plans with our research strategy – can you give us a little snippet of what we can expect?
Saurabh: We already have such a great core in terms of thought leadership, coverage areas, clients and readership, brand, and data that gives us the ability to influence and shape the market. So I want to leverage our assets and IP to focus on serving our clients…understand their challenges and provide relevant and real insights.
Our focus should be on making research ‘real’ for our clients especially concepts such as RPA, digital, AI and blockchain. Help them differentiate between a pitch and delivery, go beyond the hype, be realistic yet provocative. We should complement our in-depth blueprint reports and vendor analysis with real-life client experiences, go deep in a set of chosen coverage areas, and expand coverage of niche and emerging players with a potentially disruptive value proposition. I also think we could help our clients across three horizons: “act now”, “watch out”, and “investigate”. I want to drive our agenda to do just that.
Phil: And finally, is the analyst industry as exciting as it was 10 years’ ago?
Saurabh: Perhaps even more exciting but this is just day 2 for me…
Let’s turn that common lament we hear of a “talent shortage” on its head. What if you created a pipeline of talent that fit the needs of your business as it is growing and changing? While at the Infosys Confluence event recently, I heard about how AT&T has been taking steps for the last two years to create the very workforce it needs to achieve its vision.
First, determine what skills and capabilities your workforce will need in the future
“Based on industry and corporate direction, we chose six areas, including big data, IP networking, and software-defined networking, that we specifically want to attack as the skills of the future,” shared Candy Conway, VP, Global Managed Services Operations, Business Solutions and International at AT&T.
AT&T defined a set of roles that map to these areas, determined the associated competencies, and evaluated employees against the future landscape. They identified over 100,000 employees who will need to have a different or a more varied or developed set of competencies than they have today. “We then developed a roadmap and plan for getting these professionals into a relevant and meaningful career path that maps to the future of the company and the industry,” said Candy.
AT&T is a little over two years into this program. At this point, each employee has a prescriptive program managed through a learning portal – it identifies the role they are in currently, the one they target the future, the associated competencies for each role and the learning and education path to get there. For example, an employee could be in the network center and want to be a software engineer, and has a learning path mapped out.
The nuances of the skill areas also change quickly. “It used to be that skills would change a decade at a time, and that’s now accelerated,” said Candy. AT&T designed a program that would offer a number of options and flexibility – from internal designed and led courses, to “nano-degrees” in niche areas like web development and virtual reality to online master’s degrees from Georgia Tech and social-media based programs with badges (157,000 options) awarded as people complete courses.
Investing in future skills is of value to the employee and the company
This plan is mapped to what roles that AT&T believes it needs to have in the future…. so employees can look for open roles and bid on the ones they want to fill. There are no guarantees that these roles will be filled by employees desiring them at AT&T, but the program still provides an advantage to the employee since AT&T is defining these roles (such as data scientist) with a forward-looking view, and therefore helping employees develop these competitive and marketable skills. Certainly, having invested in the person’s training, AT&T has an interest in keeping these people in-house and this is a way of creating loyalty, stickiness and a workforce of the future.
This kind of investment can help a company attract and keep the “best and brightest” with the most potential for helping grow a company. Individuals who feel a company cares enough to invest in their talent development, keep their skills relevant (and competitive), and give them options in a career are more likely to stay with that company. AT&T also will have skills relevant to the future – the future workforce – without having to go out and ‘find them’.
The bottom-line: Become a learning organization in order to be relevant to your customer base, stay competitive, and grow.
Take a look at the vision for your company. What do you want to be able to deliver to your customers? What experience do you want to create for them? What outcomes matter over time? Determine what roles and competencies, and what training, education, and mentoring will develop your workforce to achieve it.
Businesses need to be increasingly agile to address the rapid changes driven by consumer expectations and digital technologies. That means employees also need to be agile – and managed in a way that encourages and rewards-based learning. The market is increasingly competitive for candidates who have future-oriented “soft skills” like critical thinking, problem-solving, and creativity, and the ability and interest in learning. This program provides a model for how a well-established, “legacy” brand can embrace a learning culture to enable an agile workforce relevant for competitively positioning the company for growth long-term.
“We are a customer experience company,” declared Chris Lord, Global Head – DigiCX; Growth, Strategy, and Marketing at Hinduja Global Solutions (HGS). This was in response to a discussion about HGS’ decision to partner for most of its tools and technology rather than to take the road of internal development. During its recent Analyst Day, the ~$550m BPO shared how it will use its expertise as a provider of customer engagement services to fuel growth and adoption of its “DigiCX” vision. HGS focuses on a suite of solutions aimed at finding the right balance between digital and traditional customer engagement for a unified customer experience.
DigiCX aims to guide the customer to an answer regardless of channel or device. Components include:
DigiWEB: Website self-help that maps out the common issues and has resolutions built in, including videos (made by HGS) for demonstration. One client engagement cited a 97% resolution rate using DigiWEB self-service.
DigiMessaging: A chatbot that works inside messaging apps (What’s App, Facebook Messenger) and pivots to a live agent while retaining the conversational context.
DigiTEXT: Chatbot capabilities deployed within SMS, with phone number recognition and connection to a business rules engine for greater analytics power.
What’s holding these elements together is a vision for “unified CX” designed to find the right components for each client’s customers’ needs. And with this vision is a keen interest in helping clients understand their own needs and maturity, including a digital maturity matrix assessment.
It’s refreshing to hear the unified CX discussion in contrast to the hackneyed “omnichannel.” What these solutions aim to achieve is not a CX strategy that is everything to everyone all the time—it’s about providing the customer with options, guidance and journey paths that make sense. HGS’ messaging is to intelligently integrate “BOTS and Brains” as the optimal way to transform CX to provide business impact for their clients. HGS is hoping to use its aggressive governance and engagement model to drive adoption of these solutions and become a more strategic partner with clients—engaging in quarterly strategy sessions for example, instead of just the standard QBRs. It’s wise for HGS to not try and re-invent the wheel, especially with ubiquitous technologies like chatbots. HGS leadership is well aware and transparent about the need for cannibalization of volumes and revenues that come with this kind of self-service and automated strategy—“we need to get smaller to get bigger,” is the refrain we heard throughout the event.
But when you’re making this kind of play– focused on the expertise and design, not on the platform– a service provider then needs to more clearly articulate its value and differentiation that the expertise brings. It’s the human connection and outcomes that matter—those that impact customer experience and ultimately top line growth at their clients. For example, what does an improved resolution really mean to clients in terms of CSAT, NPS and loyalty? What kind of training and differentiated talent strategy is required to serve the higher value customer interactions that leading by self-service demands? These are the questions that need to be answered in order to prove the DigiCX vision can execute, and are the next steps in HGS’ journey as a customer experience company.
Over the last few years, it’s been almost impossible to attend an IT Operations conference without Enterprise Service Management (ESM) taking up more than its fair share of the agenda. Before joining HfS, I’d spent about four years covering the trend in its various forms as both a practitioner and an analyst. So it came as a bit of a surprise to see such a huge gap between the businesses I’m covering now to those I had in my previous role.
For the clients and companies I follow now, trends like ESM and Shared Services are old hat – they’ve moved on to other more advanced forms of aligning business services. Whereas for those I worked with in my former role, the trend is only really starting to take shape now.
To best exemplify this difference between organisations, I’ll tell a quick story about the last presentation I gave before joining HfS.
At an ITSM conference at the start of the year, I took to the stage to deliver a presentation using the huge amount of data I’d collected over the years to paint a picture of trends in the industry, one of which happened to be ESM. I argued that by the end of the year up to 85% of organisations will be exhibiting some form of it – from simply sharing best practice right through to the formation of single shared service centres. The audience responded to the prediction with a few reassuring nods. Crucially, no-one chased me off the stage, although a few did come up after the presentation to utter “that was brave” before patting me on the back and walking off.
Ultimately, though, I stand by the prediction, and I continue to do so in the safe harbors of HfS, the home of the Digital OneOffice™ concept. According to HfS experts, ESM is just one fundamental of the framework. A stop on a much larger journey to truly embrace digital transformation. In support of this, they have plenty of data and analysis which, by happy coincidence supports my “brave” prediction. We can pool the dynamics into two camps – which for anyone with a passing interest in economics will recognise: Supply and Demand.
Demand: Business leaders see greater back-office alignment as critical to their success
First of all, we have demand, and this demand is coming right from business leaders at the top. HfS research shows that there is a considerable appetite amongst leaders for improved alignment of business services so much so that it’s considered to be mission critical by 31% of executives, while 48% believe it to be of increasing importance. While the evidence suggests lower ends of the senior leadership team are embracing it with the same vigor, it’s more than reasonable to suggest the demand at the C-Level will have a considerable impact on the shaping of the modern business environment.
Supply: Providers are shoring up their brains and brawn to build services that deliver greater alignment
Encouragingly, we’re also starting to see evolution in the business services supplier ecosystem. Take Atos’ recent acquisition of Engage ESM – a specialist provider in the field of enterprise service management technology and consultancy – that will add the brains and brawn of 150 ESM specialists to their offering.
Similarly, take the ambitions of ServiceNow to carve up a much larger chunk of business services. Launching from its stable footing in the ITSM space and no doubt leveraging it’s almost ubiquitous partnering of all large IT Service Providers to build a value proposition that takes what it does best in IT and apply it to the rest of the back office.
I have no doubt we’ll soon see even more providers aiming to match their services with the increased business demand.
Bigger Picture: We’ve got to get this right!
Outside of the evolution of supply and demand dynamics, there’s a much greater force at play – the drive towards a digital economy. The source of pressure on modern businesses that will see some succeed and others fail. Crucially, intelligent and aligned business services are the backbone of successful digital transformation.
For some of the organisations I have met over the years, truly aligning back-office services sounds like a pipe dream. However, for HfS, the thought leaders who designed the Digital OneOffice framework, the roadmap is clear, and if businesses want to survive in the modern digital economy, they must get their back office ducks in a row. Without back office alignment, it won’t be a robust enough platform to provide the agility needed in the digital world. By using technologies and providers of analytics, automation and the digitisation of resources and processes, businesses can break down siloed legacy operations to build efficient end-to-end business processes – the perfect platform for business agility and innovation.
So hopefully, the bold prediction I made a few months ago isn’t way off the mark. At least that is assuming businesses don’t swiftly change their minds and yearn for a siloed back office, supporting traditional communication channels and processes because “we’ve always done it this way”. Nevertheless, in a year were political pollsters and researchers have been just as surprised by the results as the winners, I may hold back on celebrating for a little while yet.
Bottom Line: Aligned Business Services are the backbone of the Digital OneOffice – companies need to get this right to survive in the digital economy.
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 NeSCom which stands for the New Standards 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.
Phil: Now 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).
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.
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.
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.
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.
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. (And this McKinsey piece entitled “Burned by the bots: Why robotic automation is stumbling” has since been published… well worth a read).
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 the ignominy of not being able to scale at the level it needs, with several of its clients and projects being either aborted or moved onto other solutions
Buyers are backed into a corner with broken delusions of automation grandeur as their CoEs fail. Buyer leaderships are being fed all this rosy information and are under incredible pressure to devise and execute an RPA strategy, with some sort of set of metrics, that they can demonstrate to their operations leadership. Many are quickly discovering they simply do not have the skills inhouse to set up automation centers of excellence and are frantically turning to third parties to help get them on the right track.
Outsourcing consultants are selling RPA before they can really deliver it. Sourcing advisors are claiming they are now “RPA experts” who can make this happen, while struggling to scale up talent bases that can understand the technology and deal with the considerable change management tensions within their clients. RPA is murky and complex, and not something you can train 28-year-old MBAs to master overnight. Meanwhile, we are seeing some advisors simply do some brokering of RPA software deals for small fees, only to make a hasty exit from the client as they do not have the expertise to roll-out effective implementation and change management programs.
RPA specialist consultants few and far between. Pure-play RPA advisors are explaining this is not quite so easy and requires a lot more of a centralized, concise strategy. There are simply not enough of these firms in the market, especially with Genfour having been snapped up recently by Accenture. With only a small handful of boutique specialists to go around, these firms can pick and choose their clients and command high rates.
Service providers are setting the pace, but will destroy each other in the process, making it challenging to source the right RPA capabilities. Service providers are claiming they can implement whatever RPA clients need, but are not willing to do it at the expense of reducing their current revenues. Meanwhile, smart service providers are aggressively implementing RPA into their own operations to drive down their delivery costs and reduce their own headcount, and many are already claiming 10-20% of their delivery headcount has been reduced. So we can expect to see providers aggressively attacking competitive clients with automation-led solutions that should create unbearable pricing pressures for service providers looking to retain the talent they need to implement this stuff. Hence, services providers will be hell bent on destroying each other and the winners will be those who eventually succeed in winning more work than they lose amidst all the destruction.
Half of enterprise buyers want help from their service providers when it comes to RPA and cognitive. When we privately polled 60 senior outsourcing buyers, at the recent HfS New York Summit, on what would improve the quality and outcomes of their current services relationships, the answer was pretty conclusive – half want to work with their providers to rollout their automation and cognitive roadmaps, begging the question why half of this famous 96% of RPA customers feel they need help from third parties if they are already so satisfied with their current RPA experiences?
The Bottom-line: It’s time to stop pandering to the hype merchants and get real about the true challenges of RPA
The biggest issue threatening the real progress of RPA is the sheer deluge of misinformation that is being churned out to the poor unsuspecting customers. I cannot tell you how many have called us up at HfS bemoaning the fact their CFO has just returned from a conference and wants a piece of this 40% savings from recording manual processes in a digital loop.
Now, it may simply be that Fran has been lucky enough to have been spoon-fed references from only those highly successful clients of RPA, hence her unadulterated exuberance of its proven value. Sadly, I don’t get to wallow in such a haven of client success, and seem to have all the clients who are struggling to get this stuff moving call us up and come to our summits to share war stories. However we conclude this latest little debacle in the unraveling of the RPA odyssey, it is clear is our leading analysts need to get their research right and owe our industry the real facts, not the puffed up hype to excite the marketeers and sales people in the software and services firms. RPA impacts jobs, it impacts process effectiveness and can cost you dearly if you mess it up. It needs to be handled with intelligence and diligence.
