Ninety percent of the world’s data was created in the last two years. Data is plentiful, but its full power is often wasted. Why are so many organizations not taking advantage of all the readily available data? Most don’t know where to begin.
At the Data-Driven Decisions Conference presented by Barnes & Thornburg, Katz, Sapper & Miller, and CSpring on September 24, panelists covered topics such as data and the future of business, how to use data for marketing decisions, and information security. A high-level summary of the key factors driving effective data-driven decision making follows.
1. Define problem
In order to make data-driven decisions, organizations must first define their questions and then work backward to find the data needed to answer them. This may seem like common sense, but the opposite is often true, as organizations don’t begin with the end goal in mind.
2. Project buy-in
Data-driven decision making is a marathon and not a sprint. It’s essential to build alignment across stakeholders from day one. Each person involved must care about the problem and the outcome. Identify a few select individuals within the organization to champion the project and build excitement throughout the project’s lifecycle. A top-down approach highlighted by sustainable executive leadership often produces the best results.
3. Gather and analyze data
The next step is to assemble the data. This includes determining the analytics and reporting solution best suited to the questions and the data. The technology can be so exciting, that the original needs are forgotten. Resist the temptation to chase the shiny object. Define the problem, establish criteria, and then identify the best technology solution. Last but certainly not least, identify and perform the necessary data analysis techniques to derive answers from the data.
4. Inform policy
The data should now be transformed into actionable information. In this state, it’s ready to inform policy and help organizations make better decisions. Data can be an organization’s competitive advantage when it’s transformed into information and ultimately knowledge.
Conclusion
This is a simplistic overview of transforming data into insights. The actual process requires thoughtfulness, access, tools, and, often, the best and brightest minds in the industry. As our panel stated, knowing where to begin is overcoming the first hurdle to transforming an organization with data-driven decisions.
