These days, there is no shortage of data. We are tracked, coded and monitored from our mobile phones, as well as through loyalty programs in supermarkets and personal records.
While data, used well, can offer a significant competitive advantage to organisations that possess it, it is most often used poorly and acts as a destroyer of business decision-making, risk-taking and action for many businesses.
Here is how big data could be killing your business:
Analysis paralysis
Too often, organisations and their leaders go into ‘analysis paralysis’. This often happens when some information provides value, so the belief is that more data will be even better. Often there is a belief that if you find more data, secure more evidence, or just get some more facts, you can lower the risk of selecting a strategy or course of action. A critical question is to know what you know, know what you don’t, and know what is enough information for you to make a decision to move forward.
Data is too often used to cover people’s butts, rather than be used to make fast, effective decisions.
The difference between information and insight
Information is very different to insight. Insight is what we get by asking great questions of data. Information is the data itself. Unless we ask great questions of what the data means to us, we can simply drown in a ream of facts.
Insight leads to foresight, and this leads to strategy. Information without insight just leads nowhere. Without great questions, data is often a burden and not of much use to the organisation. Who is asking questions of the data, what questions are they asking, and why? Further, are they using data to answer questions, or simply finding questions that can be answered by the data? The first leads to insight, the second provides only limited value.
How much information is enough?
This is one of the most critical questions for a business. For any decision, how much information or data do you need to formulate a position, and confirm a path forward? This is often related to the risk tolerance profile of the executive and the organisation. Too little information leads to risky, poorly evaluated strategy. Too much information leads us to analysis paralysis, and risk-averse behaviour (that can limit or miss opportunity).
The difference between correlation and causation
Data provides the capacity to draw many insights and conclusions. However, a trap is to mix up causation (X leads to Y) and correlation (X happens when Y happens). Most data cannot show causation, but may show strong correlation. Consider the data that shows that shark attacks increase as ice cream sales increase. Should we ban ice cream sales to save lives? (Or are they both simply related to how people behave in hot weather?)
Confidence versus certainty (risk appetite)
Data can give you a look at what happened, and may be able to provide you with a measure of confidence that a pattern may repeat, but it can give you no certainty. All the polls said Clinton would win, but Trump did instead. The data gave pollsters ‘confidence’, but they could not predict with certainty. In your business, if you believe that your data gives you certainty, you will make poor decisions. If you search for certainty, you will never act. The risk appetite of the business must be set to encourage appropriate and thoughtful use of data to drive actions.
What you can do
- Ask brilliant questions — of your people and your data. Don’t start with the data, start with the question.
- Know how much information is enough. When do you know enough to take a course of action?
- Get the best quality data you can. Make sure it is up to date and represents the market that you are in (or know if it is a proxy market). Data can be a valuable intangible asset — protect it and use it well.
- Understand the difference between correlation and causation, and be open to errors.
Know that your business needs more than just data to be successful.
