How To Use Data For Decision Making

Data-informed decision-making (DIDM) gives reference to the collection and analysis of data to guide decisions that improve success.


  Data can come from all manner of sources, including customer surveys, business intelligence software, and third party research. One of the most important distinctions to make is between analytics and experiments. The former provides data on what is happening in a business, the latter actively tests out different approaches with different consumer or employee segments and measures the difference in response. 
Companies are using  data to make better decisions about everything from product development and advertising to hiring.  big data, experts have describe the opportunity and report that “companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors” even after accounting for several confounding factors.

You need to ask the right questions, statistical analysis will be left to quantitative analysts, managers have a critical role to play in the beginning and end of the process, framing the question and analyzing the results, questions like the following could be very useful:

1. What was the source of your data?

2. How well do the sample data represent the population?

3. What assumptions are behind your analysis? 

4. Why did you decide on that particular analytical approach? Are you Considering any  alternatives?

It is very important to also pick the right metrics because there is a difference between numbers and numbers that matter. One of the most important steps in beginning to make decisions with data is to pick the right metrics. Good metrics “are consistent, cheap, and quick to collect.” But most importantly, they must capture something your business cares about.

Also you have to know the basics of data visualization in other to  decide how to best display your data, Displaying data can be a tricky proposition, because different rules apply in different contexts.Context plays a huge role in how best to render data. it may be advisable to always show the conclusions you’ve drawn, not all the details that led you to those conclusions And  When you choose how to visualize your data, you’re deciding what type of relationship you want to emphasize.