Written by Matías Zapiola
By now, everyone has told us we must be data-driven, and measure everything to manage it. We need KPIs in our job and in our hobbies, be it competitive sports or fishing. We have watches, weights, apps, spreadsheets, and dashboards. People even measure their social network time.
It used to be that you went to the doctor once a year and had your analysis run. Now, your smartwatch tracks everything. People even measure their glucose daily. This, in turn, helps us live healthier lives. Or, at least, stay tuned and make changes before it’s too late.
Here are 10 things you can track:
In business, there are all kinds and shapes of KPIs, sometimes even too many. And the bigger the company, the more complex the KPI system. Tom Fishburn explains it quite graphically.
If you are not there yet, keep calm. If you are thinking your business isn’t data-driven, you are not alone. Not everyone measures everything all the time, not yet at least. It’s a journey, a slippery slope.
Although there are many approaches to get there, I like to think of it in three steps.
- Ask. Ask “Why?”
- Challenge the answer.
- Act.
1. Ask
How does this start? Well, with a question. A single question.
Depending on who is asking the question, it will vary. I use “why?”. It’s the most open question someone can ask. It can be answered in many ways, every child around the world asks it, and it often startles everyone or at least, makes them think. It’s the first place you have to go to change things. I often try to ask “why?” several times when dealing with data.
Example:
— We are doing quite well this quarter.
— Why?
— Because we are selling more than last quarter.
— Show me the data.
Another example:
— We should invest in real estate.
— Why?
— It’s a sound investment.
— Why?
— Because prices only go up.
— Show me the data.
Examples abound, but you get the idea. Once you start asking “why?”, you can drill down enough to get to the data.
Now it is vital, if you want a data-driven culture, to get people used to the last line. Show me the data. But to get that answer, you have to ask “why?” quite often.
Being data-driven is a game of questions and answers. It may start with “why?”, but then hops on to “how?”, “when?”, or “who?”. You need to keep that question popping. So that when mail arrives, it tells you what happened, when, how, and why. It’s very common to replace a big number with “many”, or a small number with “little”. It all begins with someone who wasn’t sure about the number or worse, was trying to be politically correct.
Example:
The first questions have relative meaning. “Little”, compared to what? “a lot”, compared to what? “Tight”, compared to what? Those words don’t help you get reliable information. You need real intel, facts, and figures, you need common ground on which to hold discussions. And the only way to do that is with data. The easiest way is asking “why?”.
The first step is to question things, and institutionalize them. Make it normal to talk about numbers, give facts, and compare ratios. There is a saying that we tend to be the average of the five people nearest to us. So, making it average to talk with facts and data, and letting people question facts and data, is the healthiest thing to do.
2. Challenge
Once you have asked the questions, it’s time to understand and confirm the answers.
Now, you’ve got yourself an answer. Kudos! What do you do?
Well, first of all, you need to check that the answer is correct, contextualize and understand it.
What do I mean by correct? Well, you are analyzing the price increase in your company and you asked your analyst about it. How much did the price increase in the last quarter? This question can have many answers.
You can do an average of all the prices of the last quarter and compare them to the average of the prices of this quarter. But also you can weigh them by the sales volume of each item. Both work, but you need to understand which analysis is correct for your business needs.
Once you have the correct answer, you need to contextualize it. Following the price example, if your prices went up you need to understand whether you need to compare that answer with the competition or inflation. Both have different outcomes and different meanings. So context is always important.
Finally, you need to understand this answer. If your price went up more than your competition your product should be better and you won’t harm sales volume. In the case of inflation, you need to understand that you are keeping your P&L in a tidy shape. Reasons and explanations are there, but you need to look for them.
Once you have challenged the data, it will be easier to make business decisions. It will be easier to understand people’s behaviors, competition’s strategy and more. You can never be worse off with more information.
3. Act
Once you confirm the answers, act on the data.
Now you know the answers to your questions. You need action. This is the hard part.
Several actions can take place here. For the first part, you can make a business decision. In the price example, you can either raise prices, lower them or confirm they are at the right level.
On your data strategy, you can build a benchmark, about other data or companies. Also, you can set up targets. This way you can keep an eye on your indicators and make faster decisions.
A more elaborate action is to build a dashboard. This way you can start to centralize your information in one place. Thus, seeing the big picture. ❗ Do it with care. Information overload is an issue.
Other ways you can act on your data might be:
🧹 Data Cleaning: you might have bad data in your systems that need to be treated.
⚒️️️️️️️ Data Modeling: You might have and outdated model built for your
️️️🏛️ Data Governance: establish who owns what and what responsibilities they have.
💡 Data Products: Build insights using your data and sell them.
🤝 Data Integration: Combine data from more sources into a unified view.
🧂 Data enrichment: Leverage the power of data by enhancing its value.
More information is always better. The only way to obtain more information is to ask for it. The only way to be sure that information is high quality is to challenge it.
And, as Van Goethe said, “Knowing is not enough, we must apply.” if you don’t act on your data, you are wasting valuable resources 😏.
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The original version of this article was written in Spanish and translated into English by ChatGPT.
