How To Avoid Data Management Overload At Your Bank

By Michael Deely

Data Management At Middle-Market BanksNo matter its size, your bank or financial institution is dripping with data. As a banking leader, you have access to nearly every type of organizational data – customer data, budget data, personnel data, competitor data and interest rate data, just to name a few.

All of this data threatens to overwhelm your operations and paralyze your decision-making. Instead, you need a data management approach that helps (and not hinders) your decision-making process. In addition, your data needs to be useful not only for you as a leader, but for personnel at every level, from the boardroom to the teller counter.

Making the shift from data overload to data management that drives your bank forward isn’t an easy one, but here are four steps to get you started:

Step 1: Determine Your Most Important Data

Not all data is created equally. Some of the data you’re collecting or organizing (or even using) is not actually helping you make better decisions or improve your banking operations, so it’s important to cut out this data clutter so it doesn’t overwhelm or distract you.

A critical first step is to determine which data is the most important for you to know and track, particularly as it relates to these key factors:
  • Customer experience
  • Products and services
  • Channels
  • Risk management
  • Employees and other personnel
Without prioritizing your data management approach, data-driven decision-making is impossible. But after you have decided on your highest priority data, you can be more confident in the decisions that follow.

Step 2: Normalize And Consolidate Your Data

Once you’ve determined the data that’s most important to your decision-making process (and ignored any other distracting data), the next step is to normalize and consolidate that data into a single system or platform to guide your decisions.

Normalization and consolidation keep you from being overwhelmed by distractions in the data collection process itself, as well as save you time and energy in the future. Investing your efforts in consolidation today makes all of your data analysis and decision-making more time effective tomorrow and for years to come.

[H3:] Step 3: Create Dashboards For Your Data

With all of your data consolidated on a single platform, take your data management to the next level of visibility by harnessing the power of dashboards. Robust data dashboards give you immediate, actionable insights into what decisions need to be made or how your bank needs to correct course.

Recalling your priorities from Step 1, build your dashboards around the Key Performance Indicators (KPIs) and Key Risk Indicators (KRIs) that keep your banking operations on track with those priorities. Your dashboards should illustrate your critical thresholds and highlight any areas that require more focus.

Step 4: Prioritize Corrective Actions Based On Your Data

At this point, the biggest challenges of data management are behind you. Now it’s just a matter of turning those data points into action – and profits – for your bank.

Using your dashboards, track the select KPIs that show the most potential for improvement, then execute short, corrective bursts of action to deliver immediate results. You should especially prioritize any corrective actions that streamline your workflows and improve your efficiency ratio, as these have long-term positive effects on your profitability.

Data overload is a serious problem for banking leaders and managers, but you shouldn’t let it paralyze your decision-making process nor slow down your process improvement efforts. Instead, start with these four steps to turn data overload into data management that fuels data-driven decision-making.

Data management alone isn’t enough to execute profitable improvements for your community or middle-market bank. Click below to download a free whitepaper from Big Sky Associates and discover how process improvement initiatives directly benefit your bank’s bottom line.

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