5 Steps for Data Informed Decisions

My father recently started a blog (https://radhakguru.wixsite.com/inthemorning); it’s more of a diary where he records the unique experiences he had in his life with beautiful messages. Although, I helped him with the initial blog setup, but soon he got the hang of the interface and started sharing the content on his own.

In one of the conversations we had, he highlighted that his blog has attracted more visitors around weekdays as compared to the weekends. He showed me a Line chart generated by the blog site to showcase the trend, the graph clearly showed seasonality of daily viewership over each week. And then he said ‘I think, I shall start sharing more blogs over weekdays, to cater my main audience.’

I smiled, my father; 74 years old ex. Govt officer, has used Data Analysis to make a Data Informed decision.

We are living in age of Analytics, and Data Analysis is no longer remained as a privilege for tech savvy few. Every day, we are using the data to make the informed decision, whether it is taking a route to our destination, or choosing best product while shopping online, making data driven decision is very common. But, as you progress towards using data to make business decision, a structured approach is always helpful, it will not only help you to fully leverage the data available, but would also help you to avoid common Data Analysis pitfalls. In following lines, I would like to lay out a 5 steps process for making Data Informed decisions:

1.  Ask – Most of the solutions fails because the problems are not defined clearly. Einstein famously quoted “If I had an hour to solve a problem, I'd spend 55 minutes thinking about the problem and five minutes thinking about solutions.” In my experience, most of times Data Analysts jumps to wrangle the data, without even having high level goals defined, which is very similar to driving the car without any idea about destination. Start with a Goal in your mind, identify the issue you want to resolve or questions you want to ask before you set out to investigate further.

2. Find – Find & work with data: Identify the data you need to answer your questions and then work out how best to collect it. Data may come from internal or external sources, or both but data must be fit for purpose and used in line with the appropriate regulations.

It is very much possible that you already have all relevant data to start the analysis, however, use this step to ensure that data quality attributes are maintained.

3. Analyse – Use data analytics techniques to explore and identify any insights. For example, visualize the data using charts or graphs to look for patterns, identify correlation and spot outliers. Refer following article as reference for building effective visualization for analysis.

Be prepared to start again or iterate, it is easy to get in the trap of what is generally known as issue of local minimum. Or in other words, finding a superficial pattern and assuming it as an insight. One needs to analyse data from various angles before any conclusion can be made from the data.

4. Interpret – Identify the implications of the data you have analysed and extract its value. Make sure you step back to check the data is not prone to bias, challenge the data and consider the picture painted by data as whole.

Say, you are targeting a new market for your product and your analysis suggests that it is the right market to launch the product. But if you have not analysed that, whether it is right time to launch the product in the new market, your interpretation might be partial.

5.  Action – Influence with data and take informed decisions or you my need to use your insights to influence others to make changes. There are high chances that you would win the support of your stakeholders if you are able to showcase the story of your data insights, i.e. you are able to back your hypothesis or claim with the data analysis.

Once you take data informed decision think about following questions:

• What need to happen next?
• What is going to be changed based on the data?
• How you ensure that progress has been made?

Data Analysis is incremental & iterative process, your actions should generate outcomes, which will help you to refine your initial questions or Ask. Once you have refined your questions, you would continue your journey with next steps of data informed decision making – Find, Analyse, Interpret and Action.

Hope you found the above steps useful in your data analysis journey. Please share your thoughts in the comments sections. Thanks for following !

Cheers,

Nitin