The Decision Maker

Eye on the Prize:Getting to Self-Service Analytics

Posted by Peter Keers, PMP on Oct 14, 2015 10:55:18 AM

Here is an all too common scenario in today’s credit union: It’s month end and the IT department is scrambling to meet the demand from business units for scheduled reports and ad hoc information requests. All long-term project work is put on hold as the staff works overtime providing information to support the organization’s critical strategic and tactical decision making.

What is the solution to ending this madness? Why not give these very same business users the capability to create their own reports and mine the corporate databases for innovative insights. In other words, provide “self-service” information capabilities to the people who are in the best position to leverage information to achieve strategic goals. 

This brilliant solution is a classic “easier said than done” situation. There are lots of pesky details to consider in implementing a self-service analytics and reporting initiative. Luckily, there are a significant number of organizations experimenting with self-service. Aberdeen Research was able to survey over 500 organizations in various stages of self-service maturity to understand the crucial elements to consider.

Data Governance

There is a balance to be struck between giving users access to too much data and not enough. At the very least, credit unions must adhere to compliance regulations to protect sensitive member data. Beyond this, it important to consider what decisions various users need to support. However, tailoring data access to the needs of each user means more than giving them only the data they need to do their jobs and restricting data that is confidential or inappropriate. The data “in between” is important to consider. Suppose the Lending Department could see not only loans data but also data for shares and investments. Creative cross-selling analyses are possible as a result.

Cloud-Based “Software as a Service” Models

Aberdeens’s research showed that high usage self-service programs were more likely to be leveraging cloud-based SaaS tools. These arrangements have the advantage of being flexible to meet changing needs as well as having the potential to deliver more robust self-service tools at a reasonable cost than strictly on-premises solutions. Credit unions often are wary of cloud-based solutions due to concerns about security. While it might take some due diligence effort to allay these concerns, investigating cloud-based self-service options should be a priority.

Analytical Know-How

In organizations with high self-service usage, Aberdeen found there were more non-technical business users who were skilled in analytics. Often, these skills must be developed in the employee population. Training programs to build these skills will be important to increase the adoption and usage of self-service programs.

Data Education

No matter where users are on the “know-how” continuum, they must also know of what data is available to them, how it is structured, and how it is accessed. All of these are basic “blocking and tackling” steps that need to be thoroughly planned out so users are fully enabled to take on their analytical tasks.

Providing the Right Tools

The Aberdeen research showed that a key frustration among users of self-service tools was that the tools fell short in the ease-of-use category.  A key to self-service success is a user community that feels confident in their ability to gain actionable insights from the data. Tools that are difficult to use are an obstacle to building this confidence. Care needs to be taken in providing tools that are the right “fit” for the given user and that the user has an adequate amount of training and support to use the tools.

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Topics: Big Data, Credit Unions, Self-Service Analytics

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