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Digital Transformation: The Perils of the “Get Digital Done” Culture | Blog

By | Blog, Digital Transformation

The “Just-in-time” methodology focuses on achieving an outcome through defined structured processes that also build organizational capabilities. “Somehow-in-time” focuses on somehow achieving an outcome, irrespective of the impact it has on the broader enterprise.

Most enterprises reward leaders who embrace “get it done” approaches. Unfortunately, the ideology is becoming part and parcel of more enterprises’ digital transformation initiatives. And while “get it done” may seem like a glamorous virtue, it is detrimental when it comes to digital.

Get Digital Done Doesn’t Build Organizational Capabilities

Everest Group research suggests that 69 percent of enterprises consider the operating model a huge hindrance to digital transformation. Leaders are in such a hurry to achieve the intended outcomes that they neglect building a solid operating model foundation that can enable the outcomes on a consistent basis across the enterprise. This leaves each digital initiative scampering to somehow find resources, somehow find budgets, and somehow find technologies to get it done. And because no new organization capability – think digital vision, talent, or leadership – is developed – these initiatives do not help build sustainable businesses.

Get Digital Done Rewards the Wrong Behavior and People

Much like enterprises’ fascination with “outcome at all costs” creates poor leaders, digital transformation initiatives are plagued with the wrong incentives for the wrong people. Our research suggests that 73 percent of enterprises are failing to get the intended value from their digital initiatives. The key reason is while the leaders are expected to “somehow” complete them, there is no broader strategic agenda for them to scale it beyond their own fiefdoms. Our research also indicates that while enterprises want to drive digital transformation, 60 percent of them lack a meaningful digital vision. They’re obsessed with showing outcomes, and cut corners to achieve them. They take the easier way out to get quick ROI, instead of getting their hands dirty and addressing their big hairy problems.

Get Digital Done Does not Align People towards Common Goals

Obsession with outcomes makes leaders leverage their workforce as “tools” for a project rather than partners in success. Because the employees are not given a meaningful explanation of the agenda and the impact, they become execution hands rather than people who are aligned towards a common enterprise objective. This ultimately causes the initiative to fail. No wonder our research indicates that 87 percent of enterprises that fail to implement change management plans see their digital initiatives fail.

To succeed in their digital transformation journeys, enterprises must put their “get it done” obsession away in a locked drawer and focus on three critical areas:

  • Build a digital foundation: Although easier said than done, this requires a revamp of internal communication, people incentives, and a shared vision of intended goals. Each business unit should have a digital charter that aligns with the corporate mandate of leading in the tech-disrupted world. And it requires strategic, yet nimbler, choices on technology platforms, market channels, brand positioning, and digital vision.
  • Have realistic timelines: Expectation of quick ROI is understandable. However, a crunched timeline can backfire. Enterprises must work towards a pragmatic timeline, and incentivize their leaders to meet it without bypassing any fundamental processes.
  • Involve different stakeholders: Our research shows that a shocking 82 percent of enterprises believe they lack the culture of collaboration needed to drive digital transformation. That means the initiatives become the responsibility of just one leader or team. And that simply won’t work. Instead of driving everything independently, the leader or team should be an orchestrator of the organization’s capabilities. This is the key reason more enterprises are appointing a Chief Digital Officer, as one of that role’s key responsibilities is serving as the orchestrator. Additionally, the team needs to leverage the organization’s current capabilities, and enhance them for the future. It should build a charter for its digital transformation initiative that includes impact on fundamental organizational capabilities such as talent, business functions, compliance, branding, and people engagement.

In their race to “get it done” and appease their end customers, enterprises have forgotten the art of building organizational capabilities that will sustain them in the future and create meaningful competitive advantage. And they can’t succeed unless they change their approach and ideology.

Does your organization have a “get it done” culture, or has it built the right organizational capabilities to achieve true transformation with digital? Please share with me at [email protected].

Why Many Banks Might Have to Dump Their Delivery Location Strategy | Blog

By | Banking, Financial Services & Insurance, Blog, Onshoring

Long gone are the days when consumers were welcomed with toasters when they opened a checking or savings accounts at their local bank. Today’s consumers don’t want toast-making capabilities from their financial institution: they want cheaper, easy-to-use Internet- or smartphone-based financial products and services, including payment applications, lending platforms, financial management tools, and digital currencies, all with hyper-personalization. Most customers are quick to make a move if their current financial institution doesn’t deliver.

So, what do banks need to do to retain their customers? Two things. First, they need to deliver the banking experience their customers are increasingly demanding. Second, they need to reconsider much of their service delivery location strategy.

What do Bank Customers Want?

Let’s first look at banking customers’ requirements for a SUPER banking experience.

Few, if any, banks have the ability to deliver on these requirements. So, they’re increasingly partnering with financial technology start-ups – popularly known as FinTechs – to meet customers’ expectations.

This brings us to the second thing that banks need to do to retain and grow their customer base: reconsider much of their service delivery location strategy.

Cracking the Service Delivery Location Strategy Code

With innovation and personalization topping customers’ list of banking requirements, banks can no longer rely on the same location strategy they’ve used to deliver traditional functions such as applications, infrastructure management, and business processes. Why? Because FinTech requires a higher proportion of onshore/nearshore delivery compared to traditional functions and co-locating all FinTech segments such as payments, lending, and capital markets in the same region may be difficult given varying maturity of locations across segments.

To help banks find locations for successful FinTech delivery, Everest Group developed a framework – presented in our recently published research report, “FinTech Services Delivery – Traditional Locations Strategies Are Not Fit For Purpose!” – to measure the innovation potential of a location.

With the framework, banks can evaluate all aspects of innovation potential, including the availability of talent with emerging skills (such as artificial intelligence, machine learning, and analytics), adequate cost of delivery, and providers’ financial services industry domain knowledge.

Framework to Measure a Location’s Innovation Potential

To develop our FinTech Services Delivery/Locations report, we started with a list of 40+ global cities with leading FinTech investment and market activity. Subsequently, we shortlisted 22 locations based on multiple criteria including overall investment, technology and infrastructure, and talent. Finally, we used our innovation potential framework, coupled with other factors such as maturity of the FinTech ecosystem and cost of operations, to determine the top locations banks should consider for specific FinTech use-cases such as payments, lending, and capital markets solutions.

Here are some key findings from our location strategy research:

  • Banks may need to create a parallel portfolio of FinTech delivery locations, as they may be far different than those that are mature in delivery of traditional functions
  • A location’s innovation potential (not its cost arbitrage or delivery efficiencies) is the most important factor for successful FinTech delivery. This is because the right location will offer depth and breadth of maturity across multiple financial segments, a vibrant startup scene, agile academic institutions, tech-savvy government, ample financing options, modern technology infrastructure, and friendly regulatory environment
  • Locations that are currently regarded as nascent (e.g., West Africa, Southeast Asia, and Latin America) may emerge as attractive alternatives as the market evolves.

For more details, please see our report, “FinTech Services Delivery – Traditional Locations Strategies Are Not Fit For Purpose! Plus Profiles of Emerging Offshore/Nearshore FinTech Hubs” or contact Anurag Srivastava or Anish Agarwal  directly.

How The CIO Role Must Change Due To Digital Transformation | Blog

By | Blog, Digital Transformation

Digital transformation is sweeping through businesses, giving rise to new to new business models, new and different constraints, and presenting a need for more focused organizational attention and resources in a new way. It is also upending the C-suite, bringing in new corporate titles and functions such as the Chief Security Officer emerge, Chief Digital Officer and Chief Data Officer. These new roles seemingly pose an existential threat to existing roles – for example, the CIO.

Read more in my blog on Forbes

Process Mining for Automation Gold | Blog

By | Automation/RPA/AI, Blog

The process automation market is evolving in more ways than one. Many organizations are taking the next step of complementing Robotic Process Automation (RPA) with Artificial Intelligence (AI) solutions such as virtual agents and intelligent document capture. Others are looking deeper into their business functions with process mining and discovery software to scale automation and capture more returns from them.

Process mining and discovery solutions automate a part of automation itself. This is effectively mining processes for elusive gold opportunities for automation.

Process Miners

Process mining software has been around for a while and can be used for many purposes, but several vendors have made a name for themselves in the automation space, e.g., Celonis and Minit. These types of solutions use application logs to reconstruct a virtual view of processes. They discover business process flows and models, and provide process intelligence analytics. They can even suggest how to change a process using smart capabilities. The result is information that allows organizations to decide what process to automate next.

Some service providers have developed their own capabilities in this space as well. An example is Accenture, which uses process mining for automation as a competitive differentiator.

Valuable as it is, however, process mining also has its drawbacks. For example, it requires a lot of data. And if you want to find opportunities among processes that go across enterprise systems, you need to integrate the logs from these systems, e.g., build a data warehouse. Those of you who have built data warehouses know what a massive pain this can be.

Process Discoverers

While process miners can also do process discovery, several RPA vendors – including EdgeVerve, Kryon, and Nice – are offering new solutions. They’re using their desktop automation and action recording capabilities, complemented with AI, to capture and reconstruct what the human worker does, and then map and analyze the actions to identify opportunities for automation. Process discoverers do not require a load of application data, but they do come with their own challenges. For example, a recording may not capture the full set of relevant steps. And employees may have concerns around privacy.

The Art of the Possible

So, is it worth it to use process mining and discovering solutions despite their downsides and flaws? Yes, absolutely. But curb your enthusiasm, set expectations at the right level, and go for the art of the possible.

For example, there are many opportunities for automation within individual applications, without having to include processes that go across systems. And, you can use human intelligence to manually fill in the gaps and augment the findings of an automation discovery tool, even though doing so is going out of fashion.

With yet another category of software coming to the fore, enterprises would be right to feel that they are on a technology investment hamster wheel – there is no end to the cycle. After all, in recent years we have had the huge wave of RPA adoption. And today, in addition to competitive pressure to invest in AI-based automation, enterprises are having to evaluate process mining and discovery as well.

The good news is that automation can generate significant returns on investment. Our research and interactions with enterprises have shown this to be the case time and again. Process mining is another piece of the jigsaw, and it can help you find more automation gold.

Everest Group will be publishing a detailed viewpoint on process mining and discovery very soon. Be sure to keep an eye out for it, so you can mine it for gold.

The Three Components Your Shared Services Center Needs to Include in its Innovation Equation | Blog

By | Blog, Shared Services/Global In-house Centers

Supporting enterprises’ innovation agendas is no longer simply an opportunity for in-house shared services centers – what we call global in-house centers (GICs); it’s fast becoming a competitive imperative. And, contrary to popular perception, cracking the innovation code requires much more than just novel ideas. Success entails boarding the right people on the bus, gearing them up with the right mechanisms to drive agile decision making, and reengineering the organization’s cultural DNA to foster innovation. We’ve developed a simple approach that will help you solve this complex problem.

Let’s take a look at the three components.

The Three Components Your Shared Services Center Needs to Include in its Innovation Equation

Process

Innovation is not the product of logical thought, although the result is tied to logical structure – Albert Einstein

The first element is formulation of the right mechanisms to evangelize innovation initiatives. It requires the right idea generation mechanisms to harness unique ideas from both internal (GIC and parent company stakeholders) and external (including startups, academia, and service providers / specialists) ecosystems. A critical part of this is evaluating the strategic rationale for the partnership. While some shared services centers partner with third-party providers and start-ups for talent augmentation and skill acquisition, others leverage the connections to develop domain expertise or increase the speed of innovation.

Another essential component, specifically for GICs, is the right funding mechanism. While we see most shared services centers carving out a separate fund for innovation (which is part of the overall GIC CEO budget), we are increasingly seeing them push for a global/centralized fund where the innovation team within the center operates as an extension of the global innovation team(s), and is funded by centralized global venture funds / programs. For select initiatives, we have also seen GICs securing funding from business units and driving project-based innovation initiatives.

The third component here is timely deployment of robust governance mechanisms. Shared services centers need to adopt a disciplined approach to rigorously track performance and incorporate remedial feedback on a continual basis. This not only helps to assess the effectiveness of activities, but also guides allocation process for resources, and helps assign accountability for actions/responsibilities.

People

Innovation has nothing to do with how many R&D dollars you have. When Apple came up with the Mac, IBM was spending at least 100 times more on R&D. It’s not about money. It’s about the people you have and how you’re led – Steve Jobs

Involving the right people in the right team structure is the second critical component. Leading GICs involve stakeholders from different parts of the organization, i.e., functional and business teams, central innovation groups, R&D departments, and corporate teams to invest time in exploring adjacent and transformational opportunities. This helps in cross-pollination of teams and enables development of a holistic solution in an accelerated go-to-market timeframe. While we have seen varied designs for innovation teams (based on organizational fit and business alignment), the common thread is the focused top-driven approach to creating structural changes, supplemented by continuous support from middle management to ensure smooth implementation.

Another key initiative leading centers are taking is remodeling their existing talent practices. They are now shifting their focus from hiring for specific “skills” to hiring for “learnability” / “thinking skills”, i.e., the ability to innovate. They are incentivizing innovation, and providing special recognition for outside- the-box thinking. We are also seeing strong innovators recalibrate their existing performance measurement metrics to align with the impact generated against the business objectives.

 Culture

“Innovation is not something you do for one afternoon a week, it’s got to be in your DNA” – Jasper de Valk and James van Thiel, Google

The third principal tenet to ensuring foundational success on the innovation journey is dedicated investment in developing a customer-centric culture with active CXO-level participation. Shared services centers are deploying multiple tools to reengineer their DNA and develop a culture that breeds innovation. Most successful examples include: gamification of programs and distinctive recognition for positive reinforcement; stimulation of an experimentation mindset and instillation of risk appetite; and adoption of flexible employment models, including remote working, crowdsourcing, and open innovation.

Although new technologies are path-breaking, we believe that the key to a GIC’s success is incremental innovation. They should keep testing small-scale POCs to demonstrate end-client value and build credibility. Successful implementation of pilots can help them instill confidence among parent stakeholders, and ensure adequate support and funding for much larger scale initiatives. This process also presents centers with an opportunity to course-correct early and drive/lead enterprise-wide digital initiatives.

If you’d like detailed insights and real-life case studies on how GICs have effectively driven the innovation agenda for their enterprises, please read our recently published report – Leading Innovation and Creating Value: The 2019 Imperative for GICs. And feel free to reach out to us at [email protected] to explore this further. We will be happy to hear your story, questions, concerns, and successes!

Video: Digital Transformation and The New Breed of CIO | Blog

By | Blog, Digital Transformation

Over the last year, it seemed that CIOs faced an existential threat. This threat was coming from new roles – Chief Digital Officer, Chief Security Officer, Chief Data Officer – as well as the business becoming more and more involved in digital transformation, and looking to inject its influence into IT.

It even got to the point early on last year, where there were questions as to whether or not the CIO’s role would continue, or would it dissolve or devolve into these different roles.

During the course of the year, we investigated this, and have come up with a strong point of view that in fact, the CIO has survived this challenge, redrawn its charter, and has emerged as a very powerful and sustaining executive role in the organization.

You know, in this new charter, what we find is there is no other executive in the organization that has the breadth of vision across all the different operating parts of the organization or the depth of resources to be able to deliver on digital transformation and support the new digital operating models that are emerging – leaving the CIO as the natural place for this responsibility to stay in.

And the new breed of CIO, therefore, is redrawing their charter to support this new vision. Now, redrawing this charter is not easy, and it requires substantial changes in organization, IT organization, as well as a substantial commitment to deepen the relationship with both the business and the board so that the CIO in the organization can play this transformative role.

I look forward to hearing from you this year on how your progress toward this new charter and your experiences as you build this very important role in your organization. 

Thanks to RPA, “Integration” is No Longer a Dreaded Word | Blog

By | Automation/RPA/AI, Blog

Many enterprises that have used Robotic Process Automation (RPA) have seen the power of digital transformation, even if only in a small way through a few automated processes. The transformational value they experience is often a tipping point that whets their appetite for even more automation and deeper levels of application integration. But, this creates a quandary about how to maintain the array of automations. Ultimately, their success depends on the scope of the centers of excellence (COEs) that maintain their automations. Let’s explore further.

Getting the Wheel Spinning – Getting that Old-time Integration Religion

I believe that RPA has helped companies that previously held back from adopting newer technology solutions see the value of a digital mindset. These converts are now finding more opportunities for automation, and greater conviction in moving to digital-first operating models.

In short, something comparatively simple like RPA helps inspire confidence and vision.

The Ironic Corner to Turn – Moving beyond what Initially Made RPA so Enticing

Once this passion is unleashed, organizations come to fully appreciate that RPA is only one tool for automating operations. Many desire to transform their high volume, fast processes, and must confront the reality that surface-level RPA integrations are often not sufficient. The next steps towards more powerful automations often include integration via connectors and APIs.

The following exhibit reflects the diversity of systems which may now need to be integrated in a digital-first operating model world. (Spoiler alert: we’ll be writing a lot more about the Digital Capability Platform in the upcoming months.) And there are many ways to go about creating the needed integrations.

 

Digital Capability Platform

 

Some enterprises have cast aside the promise of surface-level RPAs, and now use their RPAs more through APIs. This is a bit ironic and worthy of a discussion by itself, but let’s get back to what happens as the types of automations proliferate.

Holding it Together – not Firing and Forgetting

One thing that all integrations – surface, APIs, or connectors – have in common is that they need maintenance. With surface-level RPA, you need to do a lot of robot maintenance when application layouts change. But all integrations, RPA included, require maintenance for other reasons as well. The biggest is the need to resolve data ambiguities, e.g., common customer names (think Jane Smith) with similar account types requesting a temporary address change. Which record should be updated? How can this correctly propagate across all the relevant systems and processes?

This is why a COE should be responsible for all types of automations, whether through surface or other integration methods. By looking across all automations, a COE can not only more accurately maintain the automations, but also identify anomalies and conceive new ways to structure interdependent automations. Of course, adding AI-based tools into the mix adds even more API connections to manage. But AI connections are far from the only ones that will need to be managed; the landscape will become more complicated before it simplifies (yes, I’m trying to be optimistic here.)

I can hear some of you saying that the COE should be an overall digital center of excellence. My answer is a big “no.” Digital is a far broader field that often involves major legacy transformation projects. Automation is clearly a part of digital, but it is operationally focused on the practical realities that come from modernizing processes that still primarily run on legacy systems.

This is a different mindset and a different set of competencies. As a result, it is best to keep a separate automation COE focused on the details of operational processes, while separately working towards the corporate digital objectives in a broader digital office. And that automation COE’s remit should be bigger than just RPA – it must deal with the combination of all types of automations that are enabling the operating processes.

Stop Trivializing AI: It is not just Automation | Blog

By | Automation/RPA/AI, Blog

AI is certainly being used to attempt to solve many of the world’s big problems, such as health treatment, societal security, and the water shortage crisis. But Everest Group research suggests that 53 percent of enterprises do not – or are not able to – differentiate between AI and intelligent automation and what they can do to help them compete and grow. This trivialization of AI is both eye opening and frustrating.

While it’s true that automation of back-office services is one strong case for AI adoption, there are many more that can deliver considerable value to enterprises. Examples we’ve researched and written about in the past year include intelligent architecture, front-to-back office transformation, talent strategies, and AI in SDLC.

It’s been said that “audacious goals create progress.”  So, how should enterprises think more creatively and aspirationally in their leverage of artificial intelligence to extract real value? There are three ingredients to success.

Think beyond Efficiency

Enterprises are experimenting with AI-driven IT infrastructure, applications, and business services to enhance the operational efficiency of their internal operations. We have extensively written about how AI-led automation can drive 10-20 percent more savings over traditional models. But enterprises have far more to gain by experimenting with AI to fundamentally transform the entire landscape, including product design customer experience, employee engagement, and stakeholder management.

Think beyond CX

Most enterprises are confusing putting bots in their contact center with AI adoption. We discussed in an earlier post that enterprises need to get over  their CX fixation and drive an ecosystem experience with AI at the core. Our research suggests that while 63 percent of enterprises rank CX improvement as one of their top three expectations of artificial intelligence, only 43 percent put newer business model among their top three. We believe there are two factors behind this discouraging lack of aspiration: market hype-driven reality checks (which are largely untrue), and enterprises’ inability to truly grasp the power of AI.

Think beyond Bots

While seemingly paradoxical, humans must be central to any AI adoption strategy. However, most enterprises believe bot adoption is core to their AI journey. Even within the “botsphere,” they narrow it down to Robotic Process Automation (RPA), which is just one small part of the broader ecosystem. At the same time, our research shows that 65 percent of enterprises believe that AI will not materially impact their employment numbers, and that bodes well for their realization of the importance of human involvement.

And, what do enterprises need to do?

Be Patient

Our research suggests that 84 percent of enterprises believe AI initiatives have a long gestation period, which undoubtedly leads to the business losing interest. However, given the nature of these technologies, enterprises need to become more patient in their ROI expectation from such initiatives. Though agility to drive quick business impact is welcome, a short-sighted approach may straight jacket initiatives to the lowest hanging fruits, where immediate ROI outweighs longer term business transformation.

Have Dedicated AI Teams

Enterprises need AI champions within each working unit, in appropriate size alignment. These champions should be tech savvy people who understand where the AI market is going, and are able to contextualize the impact to their business. This team needs to have evangelization experts in who can talk the language of technology as well as business.

Hold Technology Partners Accountable

Our research suggests that ~80 percent of enterprises believe their service partners lack the capabilities to truly leverage artificial intelligence for transformation. Most of the companies complained about the disconnect between the rapid development of AI technologies and the slowness of their service partners to adopt. Indeed, most of these partners sit on the fence waiting for the technologies to mature and become enterprise-grade. And by then, it is too late to help their clients gain first-mover advantage.

As AI technologies span their wings across different facets of our lives, enterprises will have to become more aspirational and demanding. They need to ask their service partners tough questions around AI initiatives. These questions need to go far beyond leveraging AI for automating mundane human tasks, and should focus on fundamentally transforming the business and even creating newer business models.

Let’s create audacious goals for artificial intelligence in enterprises.

What has been your experience adopting AI beyond mundane automation? Please share with me at [email protected].

How To Know If Your Company’s Investment In Building A Digital Platform Is On The Right Track | Blog

By | Blog, Digital Transformation

When your company undertakes digital transformation, undoubtedly a primary activity will be building a digital platform. As digital transforms companies, their digital platform becomes a differentiator. Building your platform is a crucial activity, as it will enable your company to change to a new digital operating model, and that model is how your company will create new value and new competitive positioning. But digital operations and technologies are still new and evolving quickly, and the business world lacks 10-20 years of experience and benchmarking data that could help your company determine the effectiveness of your platform’s performance. This is one of the reasons so many initiatives fail. To avoid that risk, let’s look at how to understand whether your digital platform will deliver your intended outcome.

Read more in my blog on Forbes

How To Avoid Frustrating, Mistaken Approach To Digital Transformation | Blog

By | Blog, Digital Transformation

Digital transformation gives companies new opportunities to change their competitive position. Typically, the objective for using powerful digital technologies is to create new value that changes the customer experience, the employee experience or the ecosystem partner experience. However, executives become frustrated when they need to communicate to their boards or peers on how quickly they can deliver on the promises of digital transformation. We live in a world of instant gratification, agile methodologies and sprints. This leads to an impression that a company can quickly achieve a new competitive position in the marketplace or quickly get meaningful benefit from the investments. Inconveniently, this impression is not the truth.

Read more in my blog on Forbes