Monthly Archives: Mar 2019

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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Posted in: Business Process Outsourcing (BPO)Financial Services Sourcing StrategiesM&A

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Re-platforming the Hyperconnected Enterprise: AI must be led by business operators, not IT traditionalists

March 23, 2019 | Phil FershtOllie O’DonoghueTapati Bandopadhyay

If I have to listen to another technologist promoting “AI as a key component of the CIO’s agenda”, I am going to start getting a little irked… AI is not another app that can be installed and rolled out like a Workday, SAP or a ServiceNow.  I even had to listen to an IT executive asking me whether he should “leave AI in the hands of SAP as part of their S4 upgrade”.  Not only that, I noticed a well-known analyst firm promoting a webcast last week advising “CIOs how to rollout RPA”.

Re-platforming the enterprise is all about crafting the anticipatory organization

The whole purpose of AI in the enterprise is to have business operations running as autonomously and intelligently as possible, which means we need to build enabling IT infrastructure that supports the business process logic and design.  People are talking about “re-platforming the enterprise”… this is really about redesigning IT to support the business needs, to help the business respond to customer needs as soon they occur, and have the intelligence to anticipate the needs of their customers before its competitors can.  

Enterprises need to be as hyperconnected and as autonomous as possible within their business environments if they want to pinpoint where disruption is coming from, where to disrupt and how to keep reinventing themselves in an unforgiving world when we no longer have time to rest on our laurels:

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The problem for IT is that AI doesn’t come packaged in a nice box with an instruction guide

I’m sorry to be mildly offensive here, but AI and automation are only effective when they are designed to solve process and business problems, not check another box on the CIO’s resume. While it is important to keep the IT team in the communication loop so that it is ready to provide the right infrastructure and technology stacks required for operationalizing AI solutions, the steering wheel of any business application of AI must be in the hands of the businesses. Smart businesses  know their key pain areas and can identify the most relevant and feasible business cases. They own the data, they know the context, and how a process should run when it is augmented with appropriate AI techniques.  

For many firms, the day they implemented their first ERP was akin to pouring cement into their enterprise

The reality is the ERP system of the last 3 decades is no longer the system of record for ambitious, hyperconnected enterprises. It is a rigid suite of standard processes that keep when wheels on a legacy operation.  The emerging system of record is the data lake itself, when the business leaders have the ability to extract the data they need to make the right decisions, or have systems that can start to help make intelligent decisions for them.

My colleague, Tapati, has been doing some terrific work that looks at the interplay between business and IT with these emerging AI-driven environments and points to 10 prescriptive activities business leaders and IT leaders need to agree on, and put into effect, if they can genuinely develop AI capability that takes them into this hyperconnected state:

The 10 AI activities the business teams must lead to ensure AI success 

  1. Prioritize use cases from AI technology availability. The business team must prioritize AI business use cases from the initially identified list of potential AI application opportunities. The team must demonstrate its process knowledge and desired end-state scenario to help the IT team to ensure effective project coordination and outcome-setting. Using external consultants at this phase can be very effective to ensure the best business/technology fit.
  2. Develop the AI Business case: The most critical step, where the business team must set initial benchmarks, define pre- and post-process improvement metrics, and estimate target benchmarks.
  3. AI feasibility analysis and specification development: Business teams must solicit help from IT teams for their expertise with items such as technical feasibility analysis, infrastructure requirement specifications, and technology stack selection. Other areas are technology cost estimation, deployment, and production release, 
  4. AI Technology cost estimation: Developing estimates for the cost of technology stacks and solution deployment efforts must be the purview of business teams, but it requires significant and detailed input from the IT team.
  5. AI Data preparation and identification: Business teams must ensures success by identifying and preparing the data for training algorithms and building models. The team must solicit assistance from analytics and data warehousing teams.
  6. Coordinate with partners: During design phase of the target process model, the business team should must provide input to implementation partners (both internally and with their consultant/services partner) regarding ontology of the problem domain, the existing process models and rules. Teaming here with IT is essential, but the business team must define and communicate the business and process needs effectively. 
  7. AI Testing: The business team must lead testing the models against the project goals during the early POC and pilot phases
  8. Manage effective AI feedback loops: To make use cases fir for production release, the business team must provide detailed, regular feedback on the accuracy and performance. Again, they need  to work with implementation partners, which may be internal teams from an AI CoE or external partners.
  9. AI Training: The business team must be responsible for budgeting, planning and executing the training for large AI user teams, encompassing all of the staffing resources, external consultant costs, processes and task owners that are involved in the implemented use case.
  10. AI Deployment: Deployment doesn’t end once the use case is in production. The business team must continuously monitor the model’s outcomes, maintenance, and updates during the inferencing phase, and if the problem context changes with new rules or data, the team needs to add new dimensions and models and create new clusters. Users may also require retraining, especially as processes may change over time. There will also be the need to monitor change management issues, potential legal issues with data privacy / staffing impacts etc.

The Bottom-line:  AI is a business issue that must be directed and managed by business executives, supported by technology experts.  CIOs who ignore this will fail

The business team should seek help from IT in terms of infrastructure and tech stack needs, but it needs to own and run the AI projects because it owns the data, context, processes, and rules and understands the pain points.

CIOs will face an existential fight if they don't start genuinely enabling the business. The world where IT was all about mitigating outages and avoiding risk is being replaced by one that demands speed, agility, and a genuine understanding of the business.

Being tech-savvy isn't enough anymore… just knowing where to build a data center is pointless if you don't know what the rest of the business has planned. And this IT obsession of continually trying to upgrade ERP solutions, when most business units these days can handle it. That's the pitfall of the old traditional IT approach - we have to make sure we never get cemented in like that again.

Posted in: Digital OneOfficeIntelligent Automation

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Are call centers cool again? Teleperformance, Concentrix and SYKES lead the first Top Ten for customer engagement operations

March 16, 2019 | Phil FershtMelissa O'Brien

Ever since IBM sold off its Daksh business to Concentrix in 2013, "call center" has been something of a dirty word to traditional service providers and software aficionados alike. 

Since then, traditional IT services have flatlined as the focus has shifted to digital solutions, where the customer is front and center to emerging interactive ("digital") technologies. Having that ability to lead the customer front line and support those customer needs with real-time speed and intelligence is core to business operations.... and service partners which can deliver this has never been so crucial.  So are call center providers back in vogue, or is this merely a blip as we transition to a world where we don't need many human beings anymore?

The contact center operations (BPO) services industry is growing at 4% globally, despite razor-thin margins and intense competition. So, why do pundits declare the call center on the brink of implosion into a piece of software, while the stagnant IT services market escapes criticism for perpetuating a “people-centric” model? While contact center BPO growth is hardly setting the world on fire, it’s been steady over the last several years, even though the majority of contact centers worldwide are still in-house. The fact that there’s still a $65 billion market for outsourcing this work begs the question why these investments are simply going away. Contact center leaders like Teleperformance and Concentrix have recently made sizeable investments in bolstering service delivery (acquiring Intelenet and Convergys, respectively), reflecting the relative importance of this market segment. The recent development in which SYKES acquired Symphony demonstrates the optimism that automation can grow, not cannibalize, the contact center business. The latter, in particular, signals a promise that contact centers can use RPA expertise to scale and complement traditional contact center services business as they pivot to become more strategic providers.

Other large business services firms are gravitating into the customer engagement market, sensing an opportunity to disrupt deals with a hybrid intelligent automation/global talent approach. Most of the Indian-heritage IT services firms with strong BPO delivery arms are gravitating back to contact centers, as they see the potential for aligning intelligent automation and cognitive assistant solutions with their global base of talent for supporting their enterprise customers. Some examples of this are with the likes of Tech Mahindra in telecoms and Infosys with order management. Cognizant, Wipro, and HCL - for example - are also competing for call center work. BPO firms that have been more focused on non-customer centric areas are gravitating aggressively back into the market, such as WNS, EXL, Hexaware, and Genpact. Even IBM has recently flirted with a few opportunities, despite selling its call center business, and we even cam close to featuring Accenture in our new Top Ten, but the firm was very adamant that is did everything but the contact center piece.

Contact centers are ripe for a renaissance, and automation is a big piece of this transformation. The common retort that a contact center with automation is an oxymoron is false. Perhaps it’s our legacy view of contact centers and automation that is oxymoronic—and it’s time to let go of that legacy. When “digital” is ultimately about new ways of doing things, the contact center is in a more precarious and important position than ever. The contact center for companies that want to stay competitive in a hyper-connected economy must learn how to embrace intelligent engagement, using the key change agent of automation to become a strategic hub that empowers both customer service professionals and the customers they support.

Enterprises must navigate the changing of the guard for intelligent customer experience services

There is a changing of the guard happening, as HFS analyst Melissa O'Brien analyzes in her new report Top 10 Front Office Customer Engagement Services, 2019.

Click for detailed view

As the dust settles on our latest Top Ten, an assessment of the Customer Engagement Operations market, we’ve been fielding lots of questions about what this ranking means from a competitive standpoint.  Our final top ten chart was chock full of what you might consider to be the usual contact center suspects, but also sprinkled with some interesting up-and-comers, as well as familiar names that aren’t necessarily known for competing in this space --  the intelligent customer engagement services that are evolving out of the contact center. The

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Posted in: Contact Center and Omni-ChannelDigital OneOfficeCustomer Experience Management

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Is the Big 3 RPA stranglehold about to be challenged? AntWorks patiently times its move

March 03, 2019 | Phil FershtElena Christopher

RPA has passed its peaky hype and we're now staring into reality for the first time in 6 years. And it's a messy picture.... the market has largely bought into three software tools and tens of thousands of people have invested a significant amount of their time training themselves on them. 

However, beyond scripts and bots and dreams of digital workers scaling up rapidly to provide reams of value, most enterprises are fast coming to the realization that they need an actual process automation platform capability that ingests their data, visualizes it, machine learns it, contextualizes it and finally automates it.  Essentially, the whole lifecycle of data components needs to be integrated into a single platform in order to take maximum advantage out of automating processes through scripts, bots and APIs.

AntWorks comes out of the closet to make its integrated automation play, taking the fight to the Big 3

Fresh off a series A round of funding with SBI Investment Co in July 2018, AntWorks has come out of the 2019 gate ready to up their profile and expand their enterprise footprint for their brand of intelligent automation. And why not choose the lovely island of the Maldives to press home its vision for its Process Automation Platform that integrates data ingestion, visualization, machine vision and RPA...

Having tracked the product for several years, and also researching the lions share of early adopters of automation products, AntWorks' machine vision is an outstanding product, and Fractal math has significant advantages over Bayesian. Visiting with the core team just last week, having them show how it can extract text from images within images is something that can provide a huge edge in the market as users wise up to what they really need to integrate data. One of their use cases involves taking a picture of a coupon flyer to find out intel on what products are being promoted, special packaging, size, flavors, dates of promo etc.. They can tell you, for example, how many ounces are on a Pringles can in an image on an image on an image (label on a can in coupon on a page of coupons).

Yes, this really is slick stuff, and last year 350 users of automation products show how AntWorks is stacking up when it comes to embedded intelligence:

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Five things enterprises evaluating intelligent integrated automation platforms should know about AntWorks

While HFS has been tracking AntWorks since early 2017, this was its first "official" analyst briefing. We took away a variety of facts as well as future direction and strategy points. Here are the five things we learned that we consider relevant to enterprises evaluating intelligent automation tech and partners:

1) Its platform offers up integrated intelligent automation – AntWork’s ANTstein platform consists of modular components including “cognitive machine reading (CMR)” sort of a computer vision meets machine learning-based smart OCR, RPA , and a smart analytics components. While these are available piecemeal, they are designed to work together. The primary client entry point today is with its CMR module. So rather than adding AI to RPA, AntWorks adds RPA to AI. HFS created our Triple-A Trifecta framework (eg: RPA, AI, and smart analytics) to make the point that you can start anywhere with intelligent automation, but our research shows most firms start with RPA and then can struggle with scale. Clients that start with CMR are tackling unstructured data which can then help unlock greater functionality with RPA downstream. ANTstein offers a path to integration which can enable end-to-end work flows and the potential for the coveted scaling of IA. AntWorks is launching its new version of ANTstein, Square, imminently.

2) Its machine learning engine leverages fractal data science rather than neural – While the sciences are different, why it matters to enterprises is that you can train some business process algorithms faster as there are finite sets of patterns and outcomes in many business processes. Fractal science tends to work best with a finite set of outcomes, rather than infinite, where neural would be more appropriate.

3) Innate process and verticalization depth – AntWorks’ leadership team came from the BPO industry (eg: Infosys BPO, WNS, Capita, Mphasis BPO), where deep understanding of business processes is essential. This deep process knowledge in the areas being automated by enterprises today is largely lacking from most AI and RPA software companies. AntWorks is applying this process focus to develop domain-specific use cases for horizontals like finance and accounting and HR and more notably industry-specific use cases like title search in mortgage or claims processing in insurance. The service provider community has really been bridging the gap between intelligent automation software and domain knowledge to create end-to-end workflows. AntWorks’ domain use cases bridge its full stack and demonstrate the potential of integrated IA.  

4) RPA innovation – While AntWorks missed the first wave of RPA, it is working to offer RPA product improvements in areas clients are grappling with such as bot productivity to ensure its relevancy. Its forthcoming Square release of ANTstein is purported to enable dynamic reallocation of idle bots and multi-tenancy of multiple bots on one machine. One of their clients in attendance at the event indicated this would be a major resource saver.

5) Bot cloning – As many enterprises have already invested in one or more of the leading RPA software players, AntWorks needs a value proposition beyond follow the leader RPA. An interesting concept they are working on is “bot cloning” – essentially replicating existing bots and porting them over to their platform. Given its current focus on unlocking unstructured data for enterprises as their lead selling point, this may create a logical bridge to RPA as long as it works. As enterprises increasingly focus on outcomes rather than the enabling technology, this may create some conversion opportunities as enterprises look for ease of integration to enable end-to-end workflows.

Bottom line: AntWorks offers a path to integrated intelligent automation, provided enterprises embrace its full stack. One more large round of funding and it will be a real force 

Go global with its platform play. AntWorks, fuelled by funding and early client success, is making a major push to take its product to market globally. While its full stack platform offers enterprises a tangible path to integrated intelligent automation, the reality is that today they are best known for their cognitive machine reading capabilities. AntWorks needs to continue to focus on its domain expertise which has the greatest potential to showcase end-to-end workflows that work across its stack – essentially showing intelligent automation in action (the Triple-A Trifecta). Currently, there are a lot of piecemeal IA tools in the market that requires custom integration to tie them together to enable straight-through processing of automated workflows. As enterprises grow weary of having to continually piece together the components that enable intelligent automation, the focus on tools will become more about what delivers the best results and can scale. AntWorks’ investment in people and expanded geographic footprint will help take the message to a broader range of prospects outside its core client case in Asia Pacific. Additionally, the firm needs work on its global channel strategy. A solid network of partners, particularly strong service partners who understand the tech and value proposition, can help AntWorks reach a broader range of prospects. 

Secure more investment funds to fight for a limited supply of talent. What's needed next is a significant second round of funding, not dissimilar to those being ingested by UiPath, Automation Anywhere and more recently Blue Prism.  The sales team, under the experienced leadership of Bill Schrank, need added firepower, and AntWorks needs to prove its RPA story aggressively... how can they truly bring it all together and negate the need for enterprises to purchase expensive RPA licenses when ANTstein provides it all for them in a one-stop solution?  And finding the talent is tough as the Big 3 currently soak up any semi-decent professional with a pulse capable of understanding and communicating the value of integrated automation.

Combat "RPA fatigue" to re-energize a weary and frustrated market.  Too many enterprises have been oversold the same old story of no-code and the fact this is supposed to be "easy".  So Ash and his crew need to make the case that clients of AA, BP and Ui can jump ship without losing face.  In addition, weary service providers and advisors need to be convinced to put similar resources into AntWorks that they already have into the others.

Posted in: Analytics and Big DataRobotic Process AutomationIntelligent Automation

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