5 Essentials for Implementing Data-Driven Decision-Making

 

According to NewVantage Partners' 2018 study of senior executives, 73 percent of respondents indicated big data projects had provided demonstrable benefits. This value has shown itself in the form of advanced analytics/better judgments, enhanced customer service, cost savings, innovation and disruption, faster time to market, and data monetization. According to an Economist research, firms that employ DDDM outperform and are more lucrative than those that do not.

 

However, there is a risk in depending too much on data and algorithms, especially when they do not align with a company's overall aims and philosophy. The Apple Card, offered by Goldman Sachs, is a recent cautionary story. Its algorithm regularly assigned lower credit limits to women and higher interest rates to males. This prompted an investigation by New York state officials.

Data must be used responsibly, and data-driven choices must be guided by the goal and values of the firm. Data is a critical company asset that must be managed properly — and decision-makers must be properly trained to exploit it.

Steps Implementing DDDM

Businesses that want to implement data-driven decision-making should take the following five steps:

  1. Determine Business Questions or Issues

    What does the firm want to achieve? Determine the most critical areas for achieving the overall plan. Is the firm attempting to evaluate an opportunity or identify a problem.

  2. Strategize and Identify Goals

    Determine what you can reasonably achieve with data. It is critical to have a defined analytical goal. Who will be in charge of data gathering and analysis? What resources will you require for the project? Will you do the analysis in-house or engage consultants?

  3. Target Data

    Determine what data should be collected and how to obtain it. What precise information is required to answer the initial questions?

  4. Collect and Analyze Data

    You'll need to set up the procedures and employees to collect and handle the data. Your organization may already have some of the information it needs. In certain circumstances, access to an existing data collection may be available for purchase. Although data is becoming more affordable and available, getting the proper data might still be prohibitively expensive. Data can be created by a number of different sources, including computer software, web sources, cameras and image systems, environmental sources, and individuals.

    After gathering the data, it must be examined to gain strategic insights. Text, audio, and video/image analytics are examples of common analytical methodologies. There are several systems available for big data analysis.

  5. Make Decisions Regarding Findings

    The analytical insights can then be translated into practical ideas and projects by key decision-makers.

 
 
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