Have we ever got so excited about a market that isn’t even yet past the half-billion dollar spend level? Are we getting over excited about solutions because of their potential before they are fully tried and tested in reality? Let’s get to the realities of RPA by examining the size and five-year forecast for software and related services expenditure:
The global market for RPA Software and Services reached $271 million in 2016 and is expected to grow to $1.2 billion by 2021 at a compound annual growth rate of 36%. The direct services market includes implementation and consulting services focused on building RPA capabilities within an organization. It does not include wider operational services like BPO, which may include RPA becoming increasingly embedded in its delivery.
RPA describes a software development toolkit that allows non-engineers to quickly create software robots (known commonly as “bots”) to automate rules-driven business processes. At the core, an RPA system imitates human interventions that interact with internal IT systems. It is a non-invasive application that requires minimum integration with the existing IT setup; delivering productivity by replacing human effort to complete the task. Any company which has labor-intensive processes, where people are performing high-volume, highly transactional process functions, will boost their capabilities and save money and time with robotic process automation. Similarly, RPA offers enough advantage to companies which operate with very few people or shortage of labor. Both situations offer a welcome opportunity to save on cost as well as streamline the resource allocation by deploying automation.
The bottom-line: RPA provides the building blocks for digitizing rudimentary processes in the digital underbelly, but the broader market for intelligent process automation is more than 10x the size
Stay tuned for our broader forecast for the global Intelligent Process Automation market, which is in the final stages of its fine-tuning, as the expenditure enterprises and service providers are making their internal teams to learn how to automate business processes intelligently, the internal training and development, pilot projects and trial implementations, is so much larger than simply software licences and third party professional services to work the software effectively.
Net-net, we have to be realistic about the value RPA brings to enterprises today, versus its potential for the future. RPA’s value for most of today’s early adopters lies in the digitizing of rudimentary manual processes. It’s a starting point for designing the underbelly that enables a digital OneOffice environment:
Digital effectiveness is all about organizations enjoying real-time process flows forged through the elimination of manual process break-points and intelligent linking of data patterns across the front and back offices. RPA is a critical building block in facilitating this journey, but ultimately it’s the whole OneOffice, not the sum of the parts, that matters for true real-time effectiveness. This is about one integrated organization unit, where teams function autonomously across front, middle and back office functions and processes to promote real-time data flows and rapid decision making, based on meeting defined outcomes. In the future… front, middle and back offices will cease to exist, as they will be, simply, OneOffice, and RPA has a critical role to play supporting the building blocks. However, the market is still very young and we’re only at the start for so many organizations, so let’s not get too carried away until we see really robust solutions with proven ROI and long-term business value.
In short, every siloed dataset restricts the analytical insight that makes process owners strategic contributors to the business. You can’t create value – or transform a business operation – without converged, real-time data. Digitally-driven organizations must create a Digital Underbelly to support the front office by automating manual processes, digitizing manual documents to create converged datasets, and embracing the cloud in a way that enables genuine scalability and security for a digital organization. Organizations simply cannot be effective with a digital strategy without automating processes intelligently – forget all the hype around robotics and jobs going away, this is about making processes run digitally so smart organizations can grow their digital businesses and create new work and opportunities. This is where RPA adds most value today… however, as more processes become digitized, the more value we can glean from cognitive applications that feed off data patterns to help orchestrate more intelligent, broader process chains that link the front to the back office. In our view, as these solutions mature, we’ll see a real convergence of analytics, RPA and cognitive solutions as intelligent data orchestration becomes the true lifeblood – and currency – for organizations.
Fractal Analytics’ bets, on AI and machine learning as its future, are set to be bolstered with its new acquisition of consulting and analytics firm 4i Inc.
We noted in 2014 in Profiling An Analytics Rising Star: Fractal Analytics, that “Fractal is now more bullish about its analytics consulting presence onshore, and its technology investments – a clear aspiration to move away from the offshore analytics model”. Our interactions and observations of the service provider since that time – including this latest announcement – seem to confirm our hunch about this pivot.
As one of the last few pure-plays left in the analytics services business, Fractal has come a long way from 2000 when it was set up in Mumbai, India to tackle niche analytics projects for U.S. based banks and consumer goods companies. It now has a global presence in 12 locations, serving well-known global brands such as Philips, Kimberly Clark and P&G. Fractal was already growing rapidly (e.g. it has grown at 60% CAGR over the last six years). We expect this move to add to their topline growth with an expanded base of U.S. clients and front-end consulting capabilities to aid sales efforts. In the last few years, it has aligned resources towards a long-term growth strategy focused on high-touch client interactions and machine learning and AI technology-led solutions.
Increasingly high-touch local interactions supported by global network
Along these lines, Fractal’s acquisition of 4i is interesting because it:
Brings CPG consulting chops: Analytics consulting was the critical missing piece for Fractal as it rounded out its services portfolio. With clients like Colgate, Kraft foods, Post, and Del Monte, 4i’s focus on CPG is evident. Its “foresight-driven approach” will align well with Fractal’s focus on predictive analytics that can help clients be more proactive vs. reactive with their analyses and decision making.
Improves client collaboration: 4i’s capabilities add to the high-touch client interactions that strategic analytics initiatives need to be successful. Fractal’s clients love the attention they get from the service provider’s management team and its long-standing relationships are a testament to this culture. 4i’s presence in a central location in the U.S. (Chicago) will help deepen client relationships. More importantly, this onshore presence will help Fractal’s analytics services be more impactful. A lot of analytics clients value “high touch” engagements where analysts can spend more time on-location to really understand business context and priorities and with the operations teams to get the best results.
Extends the delivery network: 4i brings operations presence in Ukraine and Mexico, which Fractal will need to build out a diversified and global delivery backbone. Analytics talent in India is increasingly in short supply as every IT service provider, analytics startup, and enterprise IT organization tries to scoop up analysts, statisticians and data scientists in the major cities. Add to it the smaller subset of machine learning and AI specializations that Fractal will need going forward, and you can see why tapping other talent hubs around the globe makes sense.
How this local/global expertise is complemented by artificial intelligence
These factors will bring some significant advantages to Fractal, particularly as it rolls out its strategy for incorporating machine-learning into its analytics solutions. Fractal has spent the last two years building out its product portfolio of machine-learning solutions and even reorganized its management structure to give it more focus. Its solutions present “here and now” practical applications to enterprise challenges around infusing insights into every business decision. For example, Fractal Analytics’ Trial Run solution helps teams run experiments on their existing datasets, to see the potential benefits before rolling out to a wider base. Its Customer Genomics “hyperpersonalization” platform is helping companies target customers with more relevant and meaningful dialogues based on individual wants and needs. Enterprise clients that are working with Fractal on these solutions have mentioned to us how valuable their partnership is to access and explore machine learning technology together in these early days.
That word – partnership – is a great way to describe the type of engagement that enterprises need with their technology and service providers to build out AI applications today. As my recent blog post on IBM Watson services pointed out, “Cognitive technology falls in the ‘innovation’ realm for most enterprises. It requires thorough experimentation, risk/opportunity assessment, project prioritization, steep learning curves on skills development, and above all, education and change management for the employee/customer base that is involved in the process.” Consulting capabilities are thus a critical part of this journey for any hopeful AI service provider. With this tuck-in acquisition, Fractal is playing catch-up to its competitors such as Mu Sigma and Accenture, whose consulting capabilities are at the forefront of their analytics services businesses.
The outstanding challenge is just that: how to stand out, particularly against better-known brands with similar capabilities
Fractal has already made investments in the actual technology, including its own R&D, and acquisitions of Imagna and Mobius Innovations in the last couple years. It has the foundational client relationships that it can leverage. 4i will help it bring all these capabilities together. However, there are several emerging AI-based personal assistants, personalization platforms, etc. that Fractal is competing with through its product group. Its key challenge will be differentiating itself in this new and increasingly crowded market.
What Fractal needs to do next is craft a vision for its AI applications and services specifically within its key verticals of CPG and BFSI instead of the familiar trap of becoming a generalist. 4i has complementary vertical strengths and Fractal will do well to leverage these and build out what HfS calls vertically-infused insights. Overall, we give this acquisition a “thumbs up” verdict at HfS, with an eye on how Fractal articulates its value as a more comprehensive analytics services provider going forward.
Whether you have successfully started working with Watson, are evaluating it, did a PoC 18 months ago and swore off it, or have an enterprise license sitting around, you have realized that Watson is not your average prepackaged software application. As IBM’s umbrella brand term for all things cognitive, Watson capabilities range from analytics to cognitive solutions and virtual agents, available as individual APIs or prepackaged products to develop Watson applications. As cognitive technology like Watson falls in the “innovation” realm for most enterprises, it requires thorough experimentation, risk/opportunity assessment, project prioritization, steep learning curves on skills development, and above all, education and change management for the employee/customer base that is involved in the process.
When you’re working with a service provider through this journey, chances are they are on the same learning curve because of the newness of the cognitive market for business use. While IBM is taking Watson to market through its GBS organization, Watson APIs and products are being used by business and technology services providers in a variety of ways (see our POV paper on this subject here). IBM Watson technology has been around officially for a few years, and PoC projects are the norm so far. However, HfS hears a lot of industry optimism and “gearing up” for 2017-2018 being the years of more substantive implementations through this growing network of services partners.
Considerations for using Watson services
As you explore Watson in your organization:
Understand where and how your service provider is investing in Watson to offset cost: Perhaps the biggest barrier to Watson adoption for enterprises has been its high price tag for entry. Service providers have been trying to circumvent this by exploring options to host the Bluemix and Watson licenses plus external databases. Their clients can then access both the technology and data, particularly for proprietary solutions where cognitive APIs are being leveraged. Enterprises that already have access to the Bluemix cloud computing environment are getting started with Watson on it as an incremental investment. As Microsoft Azure, Amazon AWS and other competing cloud environments all have their own machine-learning technologies, the decision to which cognitive ecosystem you go with will likely be influenced by these larger technology-buying decisions.
Find the provider that Is collaborating with IBM in areas that matter to you: Watson APIs and products are being constantly revamped, retired, and regrouped and it will help to have advance knowledge from a service provider that is deeply involved with IBM in advancing specific areas. We heard instances of how by providing feedback to the IBM Watson product development team and working collaboratively, some service providers influenced the release of new functionalities that benefitted their clients’ projects directly. Look for the connections that your service provider team has been able to establish that could impact your particular use cases.
Find the Service Provider That Is Investing in Your Vision – Or Using Design Thinking to Help You Develop One: Even in these early days, we see industry, functional, and technological strengths developing among service providers. The experience gained and customization achieved with specific solutions – like Hexaware’s superannuation bot or Accenture’s mortgage advisor Collette – are valuable to companies that have already outlined these areas for Watson or are looking for new levers for value to their business and customer base. In areas where there is not a relevant standard solution, your leadership team will often have competing priorities. Consider service providers that offer Design Thinking workshops to establish the top business priorities, the process and technology roadmaps, and the definition of your own version of a future-state with an “augmented workforce”.
Don’t Underestimate the Power and Influence of Naysayers – Educate Them First: As shared by a financial services VP, “Internal stakeholders require fundamental lessons on what Watson is and isn’t…Our skeptics didn’t fully understand what cognitive or data mining benefits Watson brings; we should have expected it earlier on and addressed it head first”. Without aligning organizational buy-in, companies in our research have seen significant slowdowns in each stage of their projects. Make sure your key representatives understand the breadth of the technology and its suitability to your use case before kicking off and then check in regularly.
The ripple effect of Watson services
With these considerations in mind, do note that whatever cognitive initiatives you undertake will invariably impact more than one part of the business and way of working. As a department undertakes the required data curation, reference architecture, process remodelling, and rollout, it will interact with and influence other departments or processes and advance their maturity toward more intelligent operations as well. For example, a retailer could go from a production pilot in personalized shopping on its website into cognitively determined best next actions for its sales channels, then on to cognitively driven merchandising and supply network on the back end to better predict demand. The core customer and product data can be leveraged across these functions and can become a powerful way to reinvent the entire customer engagement process.
The focus on better enabling the customer and/or stakeholder experience is driving significant enterprise interest to explore Watson services.
In our latest report, HfS Emerging Market Guide: IBM Watson Services, we further explore this theme of getting started with IBM Watson – the use cases so far, the progress on and beyond PoCs and pilots and the emergent role of service providers. The investments today are helping establish new norms for people, processes, and technology that will pave the way for “industrial scale” Watson in the future.
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.
