Stop And Think Before Collecting Useless Data
In This Issue
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:
- 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.
- 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 good to know whether customers will actually use it.
- 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 review whether specific decisions turned out to be the right thing to do. Ideally this will lead to self-reflection and better decision-making, though in practice most organizations aren't very good at this kind of follow-through.
- 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 often don't take action if customer satisfaction drops but sales and profitability remain high.
- 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. 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.
Customer experience failures have many causes. Poor employee training and morale, rigid adherence to policy, broken processes, understaffing, bad design, a culture of indifference, and occasionally--very occasionally--lack of some critical piece of IT infrastructure.
But even when lack of technology isn't the problem, often the first solution a company will reach for is technology.
I think this is just human nature. Internal problems are hard for organizations to solve. Root causes can be buried deep under years of corporate politics and history that nobody wants to unearth. It's much easier to leave the skeletons in the ground and look for the technological quick-fix.
And so the company reaches for the latest state-of-the-art buzzwords and implements Big Data, EFM, Analytics, or (in an earlier era) CRM, ERP, WFM, or some other technology to solve what is fundamentally a problem with poor decision-making, policy, and/or execution.
There's no doubt that these technologies bring value and have an important role in any company's infrastructure. But the technology can't solve a problem where the root cause is people and process. Technology is just a tool, and like any tool can be used well or poorly.
For example, if you are delivering poor customer experience because your employees are not empowered to solve customers' problems, implementing Enterprise Feedback Management will not solve that problem. At best, it might make it more obvious that there's an issue with corporate policies but you're still going to have to drain that swamp to fix things.
On the other hand, EFM can be a valuable tool when your organization is ready and able to make better use of customer feedback from top to bottom.
The mistake is in thinking that the tool will, by itself, drive the needed organizational changes. Instead, implementing the technology is something companies often do because it's easier than addressing the real problems.
Technology vendors are happy to encourage this thinking: it's easier to sell a product that the customer thinks will solve all their problems. But the net result is disappointment when the big technology projects fail to deliver the hoped-for results.
We saw this a generation ago, when CRM was the hot new thing. Failed CRM implementations were so common that some pundits went so far as to predict that CRM itself would prove to be just a fad. Of course CRM wasn't a fad: eventually we figured out what CRM is useful for (keeping track of customers), and what CRM couldn't do all by itself (increase sales, make your customers happier and more loyal). Today nobody questions the value of CRM, but we also have much more realistic expectations and nobody begins a CRM project thinking it will fix deep-seated organizational problems.
In the Customer Experience world, we need to keep in mind that our problems are often not solvable by technology. Technology can help, but the root causes are usually leadership, culture, people, and processes.
The good news is that it may be difficult and slow, but the problems are solvable with the right commitment.
And you might need to dig up a few skeletons along the way.