The Customer Service Survey

Stop And Think Before Collecting Useless Data

by Peter Leppik on Wed, 2016-12-07 14:52

People are naturally attracted to shiny new things, and that's just as true in the world of business intelligence as in a shopping mall. So when offered an interesting new piece of data, the natural inclination is to chew on it for a while and ask for more.

But not all this data turns out to be particularly useful, and the result is often an accumulation of unread reports. I've known companies where whole departments were dedicated to collecting, analyzing, and distributing data that nobody (outside the department) used for any identifiable purpose.

Before gathering data and creating reports, it's worth taking a moment to consider what the data will be used for. There's a few broad categories, ranging from the most useful to the most useless:

  1. The most useful data is essential for business processes. For example, sales and accounting data is essential for running any kind of business. An employee coaching program built around customer feedback requires customer feedback data to operate. If the data is a required input into some day-to-day business process, then it falls into this category and there's no question of its usefulness as long as the underlying process is operating.
  2. Less essential but still very useful is data to help make specific decisions. Without this information the company might make a different (and probably worse) decision about something, but a decision could still be made. For example, before deciding whether to invest in online chat for customer service it's helpful to have some data about whether customers will actually use it.
  3. Data to validate a decision that's already been made may seem useless, since the data won't change the decision. But in a well-run organization, it can be valuable to take the time and effort to review whether specific decisions turned out in hindsight to be the right thing to do. Ideally this will lead to self-reflection and better decision-making in the future, though in practice most organizations aren't very good at this kind of follow-through.
  4. Occasionally data to monitor the health of the business will have value, though most of the time--when things are going well--these reports won't make any practical difference. Most tracking and trending data falls into this category (assuming that the underlying data isn't also being used for some other purpose). The value of this type of data is that it can warn of problems that might not be visible elsewhere; but the risk is that red flags will be ignored. Lots of companies track customer satisfaction, but might not take action if customer satisfaction plummets but sales and profitability remain high.
  5. Data that might be useful someday is the most useless category, since in practice "someday" rarely arrives. Information that's "nice to have" but doesn't drive any business activity or decision-making is probably information you can do without.

It may seem that there's little harm in collecting useless data, but the reality is that it comes with a cost. Someone has to collect the data, compile the reports, and distribute the results. Worse, recipients who get too many useless reports are more likely to miss the important bits for all the noise.

So before collecting data, take a moment to think about how--and whether--it's going to be used.

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