Big Bank Consolidating Vendors with Recession Risk

RPA and Self-Serve Analytics Scale Amidst Budget Cuts

ETR Insights | Daren Brabham PhD 

| February 24, 2023
Quote about Snowflake
Image Credit: Quote about Snowflake

We recently conducted an ETR Insights interview with the VP and Manager of Data & Analytics for a large financial services enterprise, who is well-versed in a broad range of database, analytics, and RPA services and providers. He details how banks are preparing for a higher interest rate and recessionary environment and how this will spill over into IT spending, vendor consolidation, and hiring. Read on to learn more about how Snowflake is overtaking legacy Oracle; Alteryx for data analytics and the coming low-code environment; the unexpected limits of Microsoft Power Automate; and how this VP's development philosophy and soft launch strategy has fueled the adoption of self-service data analytics with his organization.

Macro Overview

Our guest senses fear of an impending recession within the finance sector and uncertainty as to its length; while there is typically a delay on how banks respond to this – both on the deposit and loan side – they do already note an adjustment in risk mindset. Flush with stimulus deposits, banks were strategically forced to lend; a winddown in stimulus has led to slowing deposit growth, coupled with risk to existing loan portfolios from a rising interest rate environment. Our guest expects this change in banks' financing profiles to ripple across IT budgets in multiple industries.

Our guest suspects ETR's observed slowdown in anticipated IT budget growth may be partly attributable to organizations' focus on scale. "I would say they're disproportionate; [relative to] the growth of an organization, its balance sheet, and its income statement, the IT budget is smaller. Maybe the budget grew 4% to 6%, but if revenue increased 10%, that's actually a shrink of the IT budget." Their organization has certainly shifted its focus away from hiring more bodies to efficiently scaling.

This VP has observed some reduction in redundant vendors, primarily on an ability to adequately monitor and secure all. "We used to let whoever use whatever they wanted – a Tableau, Excel, Access, or Power BI – but there is a desire to consolidate that because, as an organization, you can't provide the appropriate security." However, this should not be taken to imply any slowdown in overall reliance on technological resources, in particular robotic process automation, which is seen as a way to stabilize and ultimately reduce overhead. "Let's invest more in this because that's replacing the bodies that we need to throw at it, and it's more productive."

While they have not observed any particular hard freeze in hiring, our guest cites disproportionately fewer new hires relative to industry and enterprise growth. IT and data analytics professionals remain in high demand. "There's an excess demand over the number of available people in the market. There are companies fighting over them." As an aside, this VP is unimpressed with recent crops of college graduates. "People coming out of college are not any more practical than people coming out of high school. It's really driven off of the individual's personal ambition to learn a particular skill set."

The Evolution of Data Analytics

Within our guest's organization, self-service analytics is expanding organically, aligning with their strategy to "soft launch" services without fanfare. "We found that people were already starting to discover and find things on their own because we had already put the data and security infrastructure in place, and so there was a desire for it." They aspire for any AI/ML, IoT, or streaming analytics project to require minimal support and be as truly "self-service" as possible. While company employees relied on simple charts in the past and were hesitant to use drill-down tools, a culture change has begun. Our guest now sees a massive jump in queries to their database, which they know are coming from user-administered dashboards throughout the business.

Of particular interest is AI/ML's capacity to anticipate customer churn. Our guest initiated a POC and can now predict with 80% accuracy whether a customer will leave within six months. Internal managers and industry colleagues previously uninterested in AI/ML are now "begging for us to get to the end result, even though we're not there yet."

Additional Vendor-Specific Commentary

RPA. Both Appian and Microsoft Power Automate are considered lower-code, but still "not easy enough to get things done." While bringing novice users into an established environment is relatively simple, both are difficult to set up and configure. Regarding Power Automate, our guest expected easier integration with Microsoft. "It hasn't been as easy. My team does use that, but it's when we don't have any other option to fill the gap." He mentioned IFTTT or Zapier as possible alternatives for small organizations, though security may not scale to larger enterprises.

In the illustration below, we see ETR's Vendor Positioning within the RPA sector, where Microsoft Power Automate dominates peers with a Net Score of 63% and a Pervasion rate of 58%. Appian is mired among the lower peloton of peers with a 23% Net Score and a meager Pervasion rate of only 10%. Although not mentioned in the above commentary, UiPath trails only Power Automate in the RPA sector with elevated spending intention levels and customer counts, as exhibited by its 55% Net Score and 38% Pervasion rate.

Surprising low-code competitors. Space is opening for low-code solutions. "The players in the ETL world may not be labeled ETL, they may be the app development companies." Our guest points to OutSystems and Appian as potential competitors and notes Azure now offers an ETL tool as well. They also have hesitancy around Alteryx's integration with data lineage. "If a small to mid-sized business is exclusively on Alteryx for ETL, I'm sure that's a wonderful tool, but obviously, we need a broad view across all different systems."

Alteryx v. Tableau + Informatica. For analytics and the general "democratization of ETL," our guest uses Alteryx. "At one point, Tableau Prep was the desired solution, but it just did not compete with Alteryx in what it can do. Being able to actually use it like an app was an advantage of Alteryx over other tools." Informatica, similarly, requires too much IT skill to administer to compete with Alteryx. However, this VP is concerned with Alteryx's company culture and future. "I think they have a challenged management culture. My perception, based on conversations I've had with people who work there, is it's not a great place to work." They have also seen a dramatic slowdown in new features and bug fixes and feel Alteryx is releasing new products without finishing up their baseline product capabilities.

Tableau v. Power BI. Tableau offers great support, a robust ecosystem, and lots of forums for problem-solving, but its lack of drag-and-drop visuals is problematic, and our guest generally favors Power BI, which he has stood up in a variety of small to medium-sized organizations. He calls himself "a big Power BI fan." However, the industry still broadly favors Tableau, which our guest doesn't fully understand; this may be because Tableau offers more flexibility and control for large enterprises.

Oracle v. Snowflake. "Historically, Oracle has been our primary go-to database, but strategically that's not got a bright future." From a reporting standpoint, our guest has moved to Snowflake primarily on its user-friendliness, product cost, and dominant market position. "[With Oracle], how many people do I need to manage that, to define constraints, keys, and indexes? I work with a 20-year veteran who's worked on an Oracle database, and I asked them to be in charge of our Snowflake instance. Let's just put it this way, he has not looked back." They find Snowflake 80% less expensive than Oracle when factoring in the IT staff needed to administer it. Oracle's solutions are seen as dated, though our guest admits most companies may not yet be leveraging their newer platforms.

Cloudera v. The Big Three Cloud Players. This organization previously utilized Cloudera and still uses them for enterprise data warehousing (EDW), but found it a problematic backend solution. For a new service, the decision ultimately came down to what is the rest of the ecosystem. As a Microsoft shop, Azure was the de facto option – in line with overall ETR data. "They’ve got the entire ecosystem that AWS just does not.”

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