The idea of actionable insights is something that has gone mainstream across different departments in any and every business due to the onset of decision-centric analytics and digital transformation initiatives at large. Today, actionable insights are at the heart of many successful business decisions, and are used to help companies grow further than ever before. Actionable insights are key to any data analytics initiatives including decision-centric analytics which are at the heart of digital transformation. Analytics centered around actionable insights can also be termed as actionable analytics. In this blog post, we will understand the concepts of actionable insights with the help of examples along with few actionable analytics tools which are used when dealing with actionable insights.
Actionable insights can be defined as insights which can help in driving decisions and taking action to achieve desirable outcomes. For example, identify or classify customers who are at the risk of defaulting on the loan. Based on the classification, banks can take appropriate decisions and act on those customers. In addition, the actionable insights can also be the KPIs which help monitor the action taken to achieve desired outcome and realign the decisions to perform different set of actions as appropriate. These insights can be used to take informed decisions and help companies grow.
Actionable insights can be derived from all form of analytics including descriptive, predictive and prescriptive analytics.
Dashboards play a key role in bringing actionable insights to the stakeholders and decision makers as they provide a consolidated view of the data and insights. The following is how a dashboard having actionable insights might look like:
There are different kinds of decisions including programmed and unprogrammed decisions and actionable insights can be used to drive both kinds of decisions. You may want to check my related post – Decision science vs Data Science to understand about different types of decisions, in detail.
Lets take a look at a very short video to understand the concepts of actionable insights with the help of a very simple example.
Actionable insights can be used to take both, programmed decisions (long-term, strategic) as well as un-programmed decisions (short-term). Note that programmed decisions are primarily driven by descriptive analytics while un-programmed decisions can be mainly driven by predictive analytics.
Actionable insights often get confused with actionable analytics. While actionable insights are based on data, actionable analytics refers to the application of actionable insights by means of various software tools and techniques.
Key performance indicators (KPIs) and benchmarks play a key role in actionable insights. Simply speaking, KPIs are insights that provide the ability to track progress of your initiatives / actions / projects. In the world of product, the product success is measured using metrics / KPIs against success criteria. The KPIs drive actions appropriately to achieve the desired business goals. Often KPIs are used along with actionable analytics tools like analytics dashboards for actionable insights on various levels. Read about KPIs and the difference between leading and lagging KPIs in this blog – Leading and lagging KPIs: Concepts & Examples.
One needs to have good clarity in relation to definition of data, insights and actionable insights. The difference between data, insights and actionable insights is the following:
In order to convert data into actionable insights, we need to start from the problem statement. The following are some of the steps which can result in deriving actionable insights from the data:
Read my related post on how to arrive at the most appropriate data analytics use cases from business problems – Business problems to analytics use cases.
Some of the key advantages of actionable insights are listed below.
One of the key risk associated with relying too much over actionable insights is confirmation bias. Confirmation bias is defined as a tendency to search for, interpret and favor data or information that supports your existing beliefs or ideas. Actionable insights are meant to help you make informed decisions based on data but if actionable insight reports reinforce what you already believed then the risk of making a bad decision is higher.
The following is listed few actionable insights examples:
The following are some tools which can be used to work with actionable insights:
Here are a few of my related posts which you would want to check out:
Actionable insights are action taken based on your interpretation of both business data and its analytics which have been combined with the experience and expertise. When actionable insights are combined with the expert knowledge you can take action based on all the data which is available to you so that any decision made has a higher likelihood of being correct. Some advantages of actionable insights include faster response times, better & informed decision making, using resources more efficiently by investing where needed etc. There are tools such as enterprise dashboard software or web analytics dashboards too which allow using actionable insight from information they provide in order to make decisions quicker or optimize processes accordingly. If you would like to more, please reach out to me.
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Very very good read. Completely answered my question on how to recommend steps for users based on insights. (for context I'm a product designer)
Thank you Bari for your feedback.