As companies work out how and where data and analysis can help them understand customers better, make processes more efficient, create higher quality products and services, and myriad other tasks, they are standing up “business analytics teams.”
There are now a host of different functional areas and business lines that fund these teams, especially as firms embrace digitalization. For example, about 55% of companies now have dedicated analytics teams in HR, a relatively new phenomenon inspired, in part, by the growth and success of those teams in Marketing, which many companies created in the last couple of years.
All this activity has led IT teams – who traditionally would have funded, run, and controlled all data collection and analysis in a large firm – to wonder whether business analytics teams are now their internal customers, like so many other colleagues, and require support, whether they are an extension of IT, or something else entirely?
Helping Business Analytics Teams on Their Own Terms
CIOs describe their new role as a “pivot” to help analytics teams do their job. Typically, that means IT provides toolsets, responds to requests to access data, or builds out a centralized data platform (such as a data lake project).
Despite this support, many CIOs in CEB’s networks say that the data scientists or analytics staff on these teams want IT to leave them alone (to choose their own tools, make their own security and architecture decisions). So in a sense they are new actors in an old story about “shadow” or “rogue” IT.
However, the most forward-thinking CIOs navigate these new relationships with analytics teams in three ways.
Always ask for the business context behind an analytics team’s request: One common scenario of crossed wires is where a business partner explains an issue to their local analytics team ands ask them to investigate. In turn, the analytics teams asks IT for access to certain data sets, which IT provides.
Later the analytics teams reports back that the data wasn’t what they needed. The missing link is often the business context of why the business partner wanted the data and analysis in the first place.
Adapt IT’s role with different enterprise analytics teams: Analytics teams vary widely in their experience and focus. Some are simply business intelligence reporting groups that have been renamed “data science” or “analytics” teams.
IT should consider all the engagement postures it can play and determine what each analytics team truly needs. Some teams will need coaching or consulting, while others may need to become fusion teams of IT and business staff working side-by-side.
Outline a better value proposition for IT to analytics teams: IT should get out of the reactive role of gate keeper or access granter.
That does not mean, however, that IT must centralize vast amounts of enterprise data in order to take a more open posture. Other approaches, such as APIs, can also make data more accessible and easier to integrate.