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Making Analytics Work

Feb 21, 2014

Most people look forward to discussing analytics with the same enthusiasm as scheduling a root canal. It is dry stuff when the discussion is focused on data points and report formats. Leave those topics to the analysts and developers. That is the implementation, not the objective.

Analytics are typically viewed as a way for management to better understand how the organization is performing. That is an important objective, but ask yourself the following question.

Would you rather have employees think about their performance and role in the organization once a year during their review, or every day?

An often overlooked benefit is that analytics are a way to shape how employees perceive their own work and their role in the organization. Analytics are an opportunity to interpret the organization for its employees and influence their perception.

  • Accomplishing this objective means meeting several needs.
  • Visible and accessible
  • Relevant
  • Understandable
  • Encouraging
  • Evolving


Making it Work

For analytics to work for employees they must be visible and accessible. A billboard only works when consumers see it frequently. If it is tucked out of the way it will have very little impact. The same is true for analytics. If employees have to navigate away from their normal activities specifically to access analytics, they will not do it on a regular basis. Making analytics available in a click or two from a page or program that employees spend significant time in, will greatly increase usage. It has to be easy.

The metrics being measured and presented must be meaningful to the employees being asked to consider them. What is relevant to one group of employees is not interesting to another. A branch operations manager needs to see staffing, workload, transaction volume, outages, etc. A loan officer needs to see bookings versus goal, weighted yield, problem loans, etc. A good analytics engine should deliver different sets of information to different groups of employees.


Good analytics should not just deliver information, they should make a point. Each chart, table or report should highlight something that the employee ought to be thinking about. Ideally, the main point is made on first impression without requiring someone to dive into the details of the numbers. Selecting the right chart styles, colors and report formats are key to making an impression as opposed to delivering data.

Generally speaking, users should be able to navigate up and down the organizational structure and have the analytics present for that level. It is beneficial for employees to be able to see how other organizational units are doing. Limiting access to the employee's unit is like a football team knowing the scores of their own games, but be unable to see overall conference standings. There is no context.

Not all metrics scale up and down an organization's hierarchy. Information that is meaningful at a branch level may not be relevant at a regional level. Information that is useful at a regional level may be misleading when scaled down to an individual employee level. It is important for the analytics engine to deliver information that is meaningful at each level. The objective is to make a point, not just deliver data. For example, comparative employee workload is meaningful at an employee and branch level, but unreadable at higher levels where there may be dozens or hundreds of employees.

It is human nature that people avoid things that they do not like. It is important that employees "like" or are at least neutral about analytics they are presented with. That means easy to access, easy to navigate, not overwhelming and attractive (or at least not ugly). It also means that the analytics need to highlight as many or more accomplishments than issues. No one wants to see bad news all the time and employees need to want to view analytics.

All analytics get stale, regardless of how well presented and targeted they are. In fact, the more frequently they are viewed, the more frequently they need to change. While the fact that things change is a constant, most of the time it is incremental. If there is nothing new then employees quit looking. Providing a mix of short term measurements and longer term trends can create a steady evolution. Metrics that are highlighted as short term in one version can be moved to a historical view in the next version.

Employees who are expected to use analytics are a good source for determining what should be next. Monthly manager or operations meetings are a good place to ask what else they want to see. As understanding grows, so does the desire for more sophisticated analysis. Discussing analytics in public meetings has the added benefit of helping those who are not looking at the information to realize that those who are have an advantage.

In an era of tight budget constraints, it is easy to make analytics a low priority. After all, they are not required to open the doors every day. Does that priority remain the same after answering the question posed at the beginning? Would you rather have employees think about their performance and role in the organization once a year during their review, or every day?


What Next?

If you do not already have a good analytics engine, we invite you to take a look at what is available in the NetXed® Automation suite. NetXed analytics are included standard as part of the StaffPro® Branch Resource Management product.