There are many articles on the importance of data collection in business. We talk about “Big Data,” “Data Mining,” “Business Intelligence,” etc. Data is the foundation of new technologies such as Artificial Intelligence and is thus an important resource for a company. However, there is little information about the risks of becoming an organization that is too data-centric.
Emphasis on Data at the Expense of Judgment
Have you ever been in a meeting and watched a PowerPoint presentation full of charts that tell a story contrary to what your intuition tells you? Looking at numbers on a report and thinking that it’s just one side of the coin?
Partial or out-of-context data can give a distorted picture of a situation. Sometimes, it is tempting to want to present data that favors us and tells a positive story: an improvement in our customer service or our productivity. The temptation is even greater when we work in a company that highly values data. What the numbers say then becomes our main success factor, both as individuals and as a department.
So what will be the trap for performance devotees? Wanting to meet goals at all costs, at the expense of long-term improvement projects. A culture of high performance and data appreciation can even encourage some to exploit gray areas to improve their results, by pushing the limits of ethics.
Anecdote
I once attended an executive meeting where we discussed national-level productivity. An engineering team presented technical solutions that would improve productivity by 2 or 3% for their site. The emphasis was solely on the process and the data, both by the presenters and by the senior executives. However, my experience showed that we could improve our productivity by more than 10% simply by rotating the supervisory team. Human factors, such as leadership and the ability to engage our employees, had a much more significant impact than the process itself. Since it was difficult to quantify management behaviors and replicate them on a large scale, they were sidelined in favor of things that were easier to measure and replicate. Imagine the loss for the company!
Our Role as Leaders
We have a role to play in promoting transparency and ensuring the integrity of our teams. Here are some examples of questions you can ask to encourage good behavior and help your team make better decisions.
- How was the data collected and analyzed? Are there any biases or limitations to consider?
- How have we verified the integrity of this information?
- What other factors could influence the results? Are there human or environmental factors that could impact the data? Can we adjust for these factors? Here are some examples:
- The absenteeism rate during a snowstorm or on the eve of a holiday
- On-time delivery during bad weather conditions
- The performance of your customer service team during a high volume of more complex cases
- Do the data presented reflect the experience of our customers or employees?
- It is sometimes helpful to dig deeper when the results do not align with your experience or instinct. As they say, there is no smoke without fire.
- What additional information or analyses might be needed to make informed decisions based on this data?
We often tend to use the mean or median to represent results. While this is useful data, it is also essential to consider the standard deviation. This indicates the variability of the data: the higher the standard deviation, the more the individual values are dispersed; conversely, the lower it is, the more the values are grouped around the mean. A high standard deviation in customer service response time, for example, may indicate that some customers are served very quickly while others wait much longer. This situation is very different from a low standard deviation, where all customers would have similar response times. The same average can thus hide two very different situations.
