Reetika Fleming
Research Vice President 
Learn more about Reetika Fleming
ServiceNow and Celonis just threw down the Workflow Platform gauntlet. The darlings of IT and process workflow execution make their joint move...
October 06, 2021 | Tom ReunerReetika FlemingPhil Fersht

The new Celonis–ServiceNow partnership blends operationalizing data science with the capability to design workflows in the cloud.  We are witnessing a determined partnership between the leading IT Service Management vendor and the leading process execution platform. This is a true first in combining an IT-centric workflow mindset with an operations one.  This is where we combine IT orchestration with process modeling, mining, discovery and execution.  And even RPA.  The likes of SAP, Pega, Appian and UiPath will be feeling very nervous right now and surely have to make massive investments to keep pace with what we’ve just witnessed.

This is the boldest move yet to automate complex data with process intelligence

Against this background, Celonis’ strategic partnership with ServiceNow is a bold step that could reshape many IT and business operations discussions across major enterprises. The announcement spans initially a reseller agreement, a deeper integration of both platforms as well as a joint go-to-market.

Notably, ServiceNow is making a strategic investment into Celonis, and partners are expected to launch joint products as early as the first half of 2022. The strategic intent is to link Celonis’ data platform with ServiceNow’s workflow ecosystem to advance toward the broad execution

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SAP acquiring Signavio is a cheap play to migrate enterprises onto S4/HANA. Instead it just handed the market to Celonis
February 01, 2021 | Phil FershtReetika Fleming

Why we think SAP acquiring Signavio is a non-event and actually frees Celonis from its SAP shackles to inspire its loyal following

The initial buzz from SAP leaders with its Signavio acquisition all points to helping its clients migrate from legacy systems onto cloud-based S4/HANA applications. While that is a worthy goal, SAP needs to embrace how to support both non-IT and IT clients with rapid process redesign, if it is to stand any chance of reclaiming former glories that are long-distant memories in today's high-octane environment. The German software giant has an IT-centric view of the world, where instead we need technology and business to come together to become fluent in understanding the data they need to be effective in their markets.  To create this data, processes need to be designed to deliver data at speed, and these need to be automated in the cloud to keep their enterprises functioning.  Once processes are flowing beautifully in the cloud, you can deploy all sorts of ML and AI tools to gather increasing amounts of intelligence to anticipate your own needs - and your customers - ahead of time.

Until a decade ago, SAP was, perhaps, the most significant brand and voice in enterprise technology.  The German software supremo was the enterprise backbone, the system of record, the “way of doing things” for the majority of the FORTUNE 1000.  Back then, Microsoft was already entering rigormortis as a decrepit office suite, SFDC wasn't much more than a fancy way of managing your contacts, while Workday was confusing everyone with “thin memory”, and Oracle was just a weird collection of tired con-fused software firms run by a guy who resembled a tech billionaire version of Donald Trump.

Since then, the SaaSy likes of Salesforce, Workday, and Coupa have long-driven a narrative that you had to run your processes in the cloud, while SAP labored to catch-up as a “Cloud player”.  Then came the digital juggernauts of Microsoft, Amazon, and Google to ratchet the world of enterprise technology into a very different place, where data is king and it doesn't matter how unstructured it is.

SAP has long-lost its enterprise appeal as the process connoisseur’s tech suite of choice

SAP is a symbol of a long-forgotten time when people’s careers were tied to it, when enterprises thought being locked-into an on-premise software suite was considered a strategically smart thing to do.  Hell, any IT bigwig worth their salt needed SAP plastered all over their resume. But those days faded away after 2010 as the cloud took over the core processes in smart enterprises.  

SAP made its long-rumored acquisition of workflow and process intelligence vendor Signavio official last week. The move has implications not only for the two merging tech companies, but also the market leader in process intelligence, Celonis, that until now, enjoyed a close and successful partnership with SAP. In addition, Celonis has cultivated many strong partnerships with the likes of Accenture, Cognizant, Genpact and IBM.  Will they gravitate towards as SAP-owned Signavio?  And will SAP’s army of customers really take this seriously enough to fight their CFOs for yet more cash to pump-prime the Waldorf machine?  The depressing answer for both SAP and Singavio is simply:  no one really cares.

Why SAP needs all the help it can get to earn credibility as a process orchestration and intelligence player

Every enterprise leader has taken a hard look at their business processes over the last year, seeking ways to streamline and automate tasks and get data on what is working and what broke in the move to remote working. What started as an exercise in somehow keeping the lights on in the pandemic economy, has started to turn into wider initiatives that will have a long-lasting impact. Many enterprises in our research have expressed that ‘there is no going back’, and post-pandemic, they will need a far smarter operating model, technology stack, and data-driven business processes. At the heart of this stack, for most companies, is a hodgepodge of various versions of aging business systems, fragmented over regions and markets, that are responsible for the majority of transactions that keep the business running.

Business leaders seeking their own glory on “digital transformation” and process efficiencies have implemented a plethora of bolt-on tools around core applications over the years, including business process modeling, workflow management, document and content management engines, and of course, robotic process automation. Process intelligence tools have been the latest addition to this mix. In particular, process mining technologies that use transactional system-log data (such as from SAP) to power their analytics and machine learning models.

Why Celonis was so good for SAP customers – and will still be for some time to come

The two principal uses of process mining tools that significantly help enterprises with their SAP estates include:

1) Helping operations leaders make the most of their current ERP  and other source systems, find process bottlenecks and inefficiencies, and redesign processes such as order-to-cash and procurement

2) Helping IT teams with systems migration, such as a move to S4/HANA, where the mining technology can be used to map and monitor as-is and to-be processes, and user adoption over time.

Just with those two points, we can see why SAP’s partnerships in this space have gotten deeper in the last few years and got to a point where SAP felt the need to directly invest in a solution of its own. Hence its acquisition of Signavio.

SAP needed to partner with the likes of process intelligence leader Celonis and UiPath (which acquired ProcessGold) to keep its technology ticking, and provide its customers more process visibility and automation. Now it has the ability to define how a fully integrated BPM, workflow, process mining, and automation capability can augment its core technology, beyond what third-party platforms and a host of SAP-specific products have been able to achieve.

Weaning any client with years of experience off of their beloved Celonis to switch to an inferior product owned by SAP is not going to happen… so good luck with that folks!

When it comes to process augmentation, SAP is lightyears behind the market.  In 2018, It made a low-budget attempt to enter the Robotic Process Automation (RPA)  market with Contextor, a small little-known France-based RPA product to augment SAP Leonardo’s intelligent technologies portfolio.  Nothing has been heard of them since, with no examples of SAP playing in the process automation space.  It’s been a bust.  So if SAP can’t make head nor tail of the most base form of process automation (RPA), why does it think it can take the market by storm acquiring a product which is ranked 13th in process intelligence software:


Simply-put, all the hard years the Celonis founders spent driving around Germany selling the software to SAP customers in a VW Camper (yes, I actually know this!), ensured that Celonis has firmly established itself as the process mining solution of choice, necessitating several years of investment, training and change management from its loyal clients. So why on earth would these process-obsessed customers flock to use the industry's thirteenth best solution?

Why Signavio? Its collaboration hub and process simulation capabilities couldn’t be more timely for operating in the pandemic economy

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HFS Vision 2025 is here: The New Dawn to become a OneOffice Organization
December 07, 2020 | Phil FershtReetika FlemingMelissa O'BrienTom ReunerSaurabh GuptaElena ChristopherSarah Little

Sorry Folks...
April 01, 2020 | Phil FershtReetika Fleming

Accenture, KPMG, Cognizant, Atos and TCS lead service delivery on Microsoft AI and Google AI Platforms
July 22, 2019 | Phil FershtReetika Fleming

We've reached a stage where we can start to assess the capability of leading service providers to deliver comprehensive services across key AI platforms, especially Microsoft's Azure AI platform and Google's emerging AI platform suite.  So without further ado, let's ask HFS' Research Vice President, Reetika Fleming, how she fared leading the two major Top 10 efforts this year...

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Reetika - how are services around AI platforms progressing?  And specifically, what have you learned with regards to Google and Microsoft platforms?

We’re continuing to see AI ecosystems evolve around the big cloud vendors – Microsoft, IBM, AWS, and Google. From our recent deep-dives into the AI services alliances developing around Microsoft and Google, I can tell you that there are different strategies at play here. Google and Microsoft themselves have their own strengths and priorities, and the SI and consulting alliance partners are collaborating with them in different ways.

  • Google’s portfolio of AI components, such as text-to-speech and computer vision, is a great starting point for a fundamental development layer. Google’s AI R&D leadership is

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Will Infosys revitalize the mortgage processing market with ABN Amro’s Stater, or is this merely sweating a commodity asset?
March 30, 2019 | Phil FershtReetika FlemingSaurabh GuptaElena Christopher

Infosys has just announced a joint venture with ABN Amro for mortgage administration services, where it will acquire a 75% stake in Stater N.V., a wholly owned subsidiary of ABN AMRO Bank N.V., that offers mortgage services across the value chain including origination, servicing and collections. The transaction is valued at $143.53 million and is Salil Parekh's second acquisitive move in Europe since his appointment as CEO a year ago. Clearly, bolstering its European presence is a big deal for INFY in 2019, gaining more "zero distance" impact with European clients, adding more innovation centers, and strengthening its local footprint and brand across Europe. 

Has Infosys finally gone all "sensible" on us?

Mortgage processing is one of the most commodotized 3rd party banking offerings, where services are heavily outsourced to offshore locations, the technology platforms are mature and robust, with a lot of focus on eliminating manual processes over the last 5-10 years.  In addition, all the major banks have been signed up. So is this the new Infosys?  Making moves

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Did Genpact Just Declare The End Of The Insurance Adjuster With OnSource Acquisition?
August 02, 2017 | Reetika Fleming

Adjusters have traditionally been a critical part of claims handling… but can their role be eliminated today? With the combined use of modern technologies, field operations and remote analysis, it is now possible to radically redefine the entire claims workflow and get better results. As the processes get smarter, the traditional roles and responsibilities of adjusters also stand to be fundamentally changed. Genpact made an acquisition announcement today that gives it the potential to play a role in this transformation. Genpact bought Massachusetts based OnSource, a property, scene, and vehicle inspection specialist that has an insurance client base in the US.

Insurance carriers in the property and casualty market have a complicated relationship with their internal and independent appraisers and adjusters, resulting in a complex, lengthy and costly process to appraise the property and settle claims. The main scenarios where carriers feel the resource crunch include:

  • Catastrophe claims and adjusting are arguably the most distressing, where thousands of adjusters will spend weeks investigating affected regions. Not only is the damage inspection time consuming, it is often hazardous, as property inspectors need to brave floods, ice storms and worse to get the job done. This is where drone image capturing is starting to play a huge role.
  • Similarly, drones can be used for appraisals in large commercial properties such as factories that need a significant time to inspect in-person. This is an area where OnSource has combined drone image capture with 3D image rendering.
  • Auto insurance needs separate triage outlets for the higher volume of small, non-complex claims. Often, carriers club appraisal efforts for all exposure types, and end up hiring expensive independent appraisers to supplement their teams for these small claims. This is another area of focus for OnSource, which offers a self-service photo-taking app for customers to submit their data through their smartphones.

Onsource’s model allows carriers to customize the level of physical/digital connectedness in the process, as it not only offers the self-service app and drone options, but also a field inspection team and a “screen-sharing” type of virtual inspection service. The likely implications for a carrier, with a partner like OnSource is that the carrier can maintain a leaner appraisal and adjuster staff, rely less on external help, undertake more desk-based evaluations, provide more self-service options for customers and potentially create more straight-through processing for certain exposure types. Thinking about the future of appraisers and adjusters, we don’t see the roles disappearing, but they will be significantly altered. You will always need teams to undertake special investigations, liaise with intermediaries, customers, and witnesses, etc. What will change is the nature of work for some, e.g. not all appraisers will want to move from field ops to desk-based writing.

What is interesting is the possibility of what Genpact as a large-scale insurance operations partner can start to offer with the addition of OnSource. This is yet another example of a service provider who is thinking beyond legacy “BPO”. Taking a step back and evaluating the entire value chain of processes and service experiences, instead of just decoupling tasks that can be done offshore/offsite. The insurance business process services industry is so mature at this point, that we are staring at this step-change in roles for service providers. Who can help carriers with the messy “feet on the street” work that takes up so much time and resources and exorbitant costs to orchestrate the evaluations done by underwriters, adjusters and appraisers? Helping prepare underwriting case files, pulling information together using remote teams has some benefit, and was the story so far. Most providers hadn’t touched claims adjudication, and work around the processing and settlement areas instead. This acquisition follows similar moves made by competitors such as EXL that acquired underwriting support specialist Overland Solutions a few years ago (read our analysis here). Genpact faces tremendous competitive pressure from its closest peers such as EXL and needed to create more differentiation in a fairly commoditized market. What is different with OnSource is that Genpact is not just taking more ownership of the process value chain, but doing so in a forward-thinking way, using modern technologies to simplify the work and the experience itself for all parties involved.

We will continue to observe how Genpact leverages OnSource’s capabilities in coming months. The acquisition is part of Genpact’s strategy to provide more “end-to-end” solutions in insurance, in particular, in P&C claims. It has already acquired claims adjudication and support services capability with the addition of BrightClaim and National Vendor in the last year. Genpact is challenged in integrating all these capabilities together, as acquisitions haven’t been its strongest suit in the past. Further, the service provider will need to put significant focus on shifting its go-to-market strategy for insurance.  Blending these additional capabilities will require Genpact to really move away from labor-based commercial constructs, which constitute more than half its insurance business today. Even if it does reorient internally to offer more business outcome-based models for claims adjudication, Genpact will need to recreate its perception, particularly for existing clients that see the provider primarily as a partner for backoffice processing. Overcoming these challenges is part of the solution to long-term growth for Genpact and all of its competitors in insurance operations. OnSource is a great start, as it brings more to the table by means of technology enablement in the claims management process, with the potential for better customer experiences that the P&C market so desperately needs.

Fractal plugs consulting gap with 4i acquisition
June 07, 2017 | Reetika Fleming

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.

Not-So-Elementary Considerations For IBM Watson Services Buyers
June 05, 2017 | Reetika Fleming

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.

Are automation PoCs leaving you in robotic limbo?
May 09, 2017 | Reetika Fleming

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

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

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

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

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

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

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

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

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

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

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

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

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