Newsletter 08/2018 - Analytics in Decision Making, Article 8

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This is the eighth in a series of articles on Analytics in Decision Making: Data-Driven Decision-Making Process - How to Ask the "Right Questions" (and Measure Them)?

2frame Analytics has here an interesting article about the importance of Analytics in the process of decision-making based on data.

Is your company actually using data to guide its decisions rather than using them to retroactively justify decisions already taken?

Companies using data to guide their decisions choose which metrics to use at the beginning of their business decision-making process, and based on their business cycle - not arbitrarily, after the business cycle is completed.

Because their leaders clearly define what success means and, above all, ask the right questions that drive the business cycle.

But how can I reach these "right questions?" Kevin Troyanos, in his article "How to Make Sure You're Not Using Data Just to Justify Decisions You've Already Made" suggests 4 steps to implement a business cycle model based on Data Analytics in a proactive and transformational way that guides your decision, instead of justifying it retroactively.

Step 1: What we really want: setting goals

Are you sure that the regular metrics are fit for your purposes? What do you really want to do and what do you need to measure to find out if you're reaching it?

Step 2: What does our data/analysis already tell us?

What do we already know about our goal? What can our currently available data tell us or advise (without justifying) on our goals stated in the previous step?

Step 3: State all the questions that come to your mind: put all the questions on the table

Now is the time to put all the questions that come to the minds of those involved in the project: the more questions, the better. It is better to map out the areas where there are uncertainties in the operation, even if these uncertainties cannot be solved.

Step 4: Choose the questions whose answers bring interesting and meaningful results to the project

With an extensive list of questions from the previous step available, evaluate, criticize, and prioritize questions that are important and that have a great potential to bring meaningful results.

Some of them may be easily implementable/answered but they will not contribute to the business (QUESTION 1), while others may revolutionize the business but are impracticable to answer them (QUESTION 2).

The focus is on finding questions that contribute to the business, although curiosities and partial improvements may be valuable for a particular situation.

Analytics permeates all the steps above and serves to support a cycle that repeats and perfects itself, so that one does not look at the rear view mirror to justify the mistakes made, but rather learns from them and improves at every new round of the business cycle.

Analytics is about solving problems, no matter what they are and where they come from.

We ask again:

Do you already use Analytics for decision-making in your company?

Read more about the subject of this Newsletter:

1) "How to Make Sure You’re Not Using Data Just to Justify Decisions You’ve Already Made", Kevin Troyanos,

Originally posted on 10/15/2018