Do More Data & Analytics Benefit or Harm Digital Transformation in FSIs?

Agility is Overrated Across the Majority of FSIs, Other FSI Digital Transformation Weekly Reads

Do More Data & Analytics Benefit or Harm Digital Transformation in FSIs?

We live in a time where it seems that an average person understands complex topics better than those in charge of government institutions. Whether it is pandemics, crime reduction, children's education, or fiscal policy, more qualifications don't necessarily lead to more effective decisions. In the past, we could blame insufficient data for ineffective decision-making. Today we have plenty of data, yet, surprisingly, our biases tend to make it even harder to agree on how to interpret it and make optimal decisions.

For financial services and insurance companies, this paradox is especially pronounced since their products are literally all about interpreting data for clients. And yet, many FSIs don’t use data when making very expensive strategic decisions to utilize it ineffectively. It’s rare to find a case for digital transformation with robust data justification, rarer still are those that don’t fall apart after a quick interrogation. In my operating, advisory, and board engagements with FSIs, I too encountered strong resistance from the executives to practice data analytics for making more effective digital strategy decisions. Here are the most common reasons:

• “We are already a top player without performing such analysis”

• “We need a data analyst who could do this”

• “The required data doesn’t exist or is inaccurate”

The lack of interest in data is not limited to KPI trees or ROI calculations (see this newsletter for estimating those metrics). During a conversation with the Head of CX at a top-10 commercial P&C carrier, I asked how she was learning about what matters to prospects. The response was disheartening: "We don’t know that, and Sales don’t seem interested to find out." I proceeded to ask if they knew the key differences between the Fortune 500 clients they had versus those they did not, perhaps from a "white" space analysis, the answer was even more concerning. "Yakov, what 'white' space analysis?.. We don’t even collect the Net Promoter Score-type feedback from the existing clients!" Our loyal readers might recall another data-related example from a Sales group featured in this newsletter. If Heads of client-facing groups are not interested in better data, it’s not surprising that some Heads of Data & Analytics feel compelled to launch new functionality anyway with the hope of eventual usage.

So, let’s explore how your classic FSI C-Suite executives make strategic decisions about digital transformation. They mostly repeat what they did in the past (note, not "what worked in the past"), or base their decisions on some exciting idea they heard from a vendor or at a conference. This is how one global insurance company spent over $20 million on a data management platform. Their Chief Risk Officer and Chief Data Officer learned from a vendor about an exciting data warehousing solution that could significantly improve underwriting effectiveness at a lower shared cost and cross-enterprise transparency. The CEO liked the vision, and the build-out began. I was asked to help persuade LOBs to join a pilot. "Were they involved in the planning phase?" "No."

Here is a typical approach as demonstrated by the enterprise data & analytics leader, Dr. Sujatha (Su) Rayburn, of a smaller FSI:

Delta Community is in the process of creating a strategic analytics center of excellence (COE) that will focus on building member centricity to bring data from all its digital channels. This can help ensure that the data is oriented towards serving members supporting member service in a more robust way. 

“Delta Community wanted to meet members’ needs at the right time, at the right place and at the right level,” said Rayburn. “The strategic analytics center of excellence will help Delta Community focus on member needs and use analytics to support member service; it will also modernize our tech stack and help us scale and perform better.”

Focusing on member-centric analytics is always a good idea, but top-down efforts such as COE and modernization are likely to lead to overbuilding. Back-office groups like Data simply can’t know for sure the optimal client-facing functionality. Digital transformation exacerbates that intuitive gap due to the higher risk and uncertainty of digital solutions.

Even within more advanced financial services and insurance companies, the lack of cross-functional operating models creates data management sprawl and analytics silos. A typical large credit card company or P&C carrier may have approximately 50 data analysts in their "customer-360" group and around 50 AI data scientists on an enterprise level. While these groups are busy aggregating data and creating analytics features, they may struggle to articulate which use cases would justify their significant burn rate of approximately $20 million each. The main challenge for these groups is usually how to get the darn LOBs to use their solutions after deployment.

In our previous newsletter, we discussed the ongoing tension between enterprise groups and LOBs and ways to resolve it. However, instead of revising their operating model, many enterprise data groups have adopted a new fix to lacking collaboration: an enterprise-wide data literacy program. Essentially, a data literacy program = scope from back-office employees who lack expertise in monetizing data * methodology from third-party trainers who never scaled relevant use cases * sessions with revenue-generating employees who don’t see a need for more data and analytics. It's like a sports coach designing a complex offensive system without consulting the players and then hiring an external trainer to force the players to use it without making any significant adjustments.

The good news is that more Heads of D&A and IT Data Management realize the ineffectiveness of top-down efforts and are increasingly demanding LOB involvement. Those FSI executives learned that more D&A efforts create an exciting environment but without eventual P&L impact, it’s hard to retain top talent and ensure personal job security. There is a proven approach to leveraging more data & analytics that delivers guaranteed benefits. It acknowledges the human tendency to avoid in-depth analysis and to disagree on facts that don't align with their incentives.

The key takeaway from D&A groups that practice such methodology: support and challenge your LOBs, but do not decide for them. Adopting such a bottom-up self-selection approach can help minimize data and analytics waste and maximize their impact. With this approach, disagreements among stakeholders in interpreting facts due to biases or politics would not derail the impactful use cases. Even if someone in the C-Suite is excited to start a pet D&A project, this operating model ensures that the right decisions are made by the right owners at the right steps, while providing everyone with an opportunity to challenge them. And in case there are no takers, the saved funds and resources can be used to teach data literacy in a local school where it truly belongs.

Agility is Overrated Across the Majority of FSIs

The most precarious phase of digital transformation is Level 3, aka the 'IT Product' operating model. At this stage, certain IT teams work faster in delivering business functionality by leveraging modern digital pillars such as Agile, API, Cloud, DevOps, and ML. Despite of the easy allure of digitization-without-transformation, this phase is also the most ineffective due to the lack of hands-on management by the Business. When IT decides on digital initiatives' scope and pivots, it usually leads to rapid overbuilding.

During a meeting with us, the LOB CIO of a leading payments company shared her excitement over the IT organization's adoption of Agile practices, stating that their delivery velocity had doubled in the last six months thanks to the regular usage of Agile routines. When asked about Business engagement, she replied that they had not yet shown increased participation. I cautioned her that their group may be delivering unnecessary functionality. She disagreed, and the meeting ended without further discussion. However, the CFO of the company reached out to us six months later, revealing that their IT costs were rapidly increasing. “We encouraged full Agile adoption in IT, but, apparently, IT had failed to connect with the Business.”

Many FSIs achieved Level 3 digital maturity in some of their LOBs five or even ten years ago, but have since failed to make any forward momentum. To make matters worse, the lack of effective business impact has led to many employees viewing "Agile" as just another passing fad and reverting back to the waterfall method. In these FSIs, the speed of decision-making (often referred to as "agility") has become synonymous with effectiveness, and executives have bought into the idea that making fast changes alone leads to better outcomes. Activities such as IT re-orgs, build-out approvals, and partner sign-ups are seen as digital-related, yet few are asking the tough questions about their ROI and P&L impact. Next time you hear an FSI C-Suite executive exalting their digital transformation achievements at a conference or on a podcast, notice what is usually missing: any discussion of North Star metrics as opposed to agility (see this newsletter for more).

The speed-agility at which internal IT activities being performed is a vanity metric, much like the number of customers in a business. It only holds value if it drives earnings, which is not the job of the FSI CIO to know. IT's primary responsibility is to support LOBs in generating earnings, so it’s Business heads who need to decide whether more agility would be worth the effort. The key to Level 3 success lies in IT rapidly but selectively preparing for Level 4 by creating shared technology services, one at a time. Rather than attempting to make IT operate in Agile from top to bottom, business-led value streams shall determine which IT capabilities are imperative to level up vs. could maintain a traditional IT Project mode.

The recommended approach requires IT executives to initially level up a select few teams instead of sending everyone to Agile training and hoping for the best. This is a practical constraint to a top-down digital transformation. Even the most advanced traditional FSIs have a wide spectrum of digital maturity among their employees. Stacking IT employees by the maturity of the digital use cases that they are capable of tackling is the best way to maximize the ROI of their efforts. This bottom-up approach inevitably creates different tiers of IT employees, so it's crucial to communicate to the organization the trade-offs of expected failures, intensive learning, and an irregular schedule, even offering individuals to self-select into this uncertain Agile journey. It's akin to Special Forces training - it may sound exciting, but the reality of what it entails and the high failure rate becomes apparent upon learning more about it.

How can IT leadership determine if a Level 3 team is ready to move onto Level 4 of digital maturity? Look for a team that has a proven track record of rapidly deploying business functionality without major issues, and where every member of the team can articulate a high-level business reasoning behind the functionality. At that point, there would be one or two Business executives who are ready to personally get involved with the inaugural value streams. In my experience, it takes a month of semi-daily in-person sessions for a value stream to take hold, and then the power of real Agile begins to shine.

Other FSI Digital Transformation Weekly Reads

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5 hot digital transformation trends — and 2 going cold

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