A type of data that companies need to collect today

In the era of digital transformation, companies are collecting almost every type of data. Financial, logistic, employee data are just a few examples. However, at least one important type of data that most businesses miss is internal “Decision-Making Data.”

Decision-Making Data

The “Decision-Making Data” is probably the most important, expensive, and complex data that every organization produces internally but rarely collected.

The main challenge is to have the data and rely on it on time but not late as in real-world tasks, and the environment changes constantly. There are a hundred tools and systems that help you execute your process and make sure that all of them can connect on the same platform.

If we need an AI-assisted decision support system for the future, we need to collect internal decision-making data today.

Thanks to digital transformation, emerging machine learning technologies, and big data, businesses and companies have made significant predictive analytics advances in the last few years.

A good example of the concept can be the company hiring plan for the next year based on the employees’ performance numbers and hiring statistics. Or costs cut for the quarter based on the revenue degradation for the previous one and the sales team effectiveness numbers.

The decision-making data is simply data generated by series of purposeful actions by an expert along with environmental data that is represented in the most effective view and aligned with the business objectives.

What Is Data-Driven Decision Making?

Data-driven decision making (DDDM) is a process that involves collecting data based on measurable goals or KPIs, analyzing patterns and facts from these insights, and utilizing them to develop strategies and activities that benefit the business in several areas.

10 Tips And Takeaways For An Enhanced Data-Driven Decision Making Strategy

1) Guard against your biases

2) Define objectives

3) Gather data now

4) Find the unresolved questions

5) Find the data needed to solve these questions

6) Analyze and understand

7) Don’t be afraid to revisit and reevaluate

8) Present the data in a meaningful way

9) Set measurable goals for decision making

10) Continue to evolve your data-driven business decisions

But the first and the most important thing is to have a leadership team with a data-driven decision-making mindset. The rest is practice, experience, and readiness to experiment with the new approaches and tools.