Data-driven decision-making (DDDM) is the process of supporting strategic business decisions with facts, metrics, and data. When combined with an intimate understanding of a company’s goals and objectives as well as a corporate culture that encourages creativity and curiosity, DDDM can be a powerful means for team members at all levels to propel the organization forward.
Many company executives understand the importance of DDDM, yet a large percentage of organizations are still in the process of becoming more data-focused. In fact, the majority of these initiatives fail because businesses focus more on the technology and less on the fundamental shift needed in the company culture needed to ensure success.
Here, BairesDev looks into how a DDDM approach can benefit companies, what stops them from being successful, and what contributes to success.
Benefits for Businesses
Work management software provider Binfire sums up the primary benefits of DDDM: “Data analysis allows companies to choose new business opportunities with a higher chance of success, generate a higher level of revenue, and prepare the business for future growth by more accurately predicting future trends.” Using data as the basis of decision-making ensures continuous progress toward goals and objectives.
The following video explains additional benefits of DDDM for a variety of uses:
But companies can only reap those benefits if they’re not hampered by common limitations such as those listed below.
- Checking for the wrong metrics. Each company must carefully determine its critical key performance indicators (KPIs) and use the corresponding data. Checking for irrelevant information will only set leaders in the wrong direction.
- Not having a suitable data management solution. Any data management solution must include the features a company needs to manipulate information in helpful ways. It must also be flexible enough to change as the company’s needs shift.
- Workers at all levels unable to access relevant data. Data is no longer solely the purview of data analysts. Employees at all levels should have access to the data that can help them make independent decisions for their departments.
- Workers not trained to use data effectively. Data is worthless without proper interpretation and analysis. Employees at all levels should be thoroughly trained in data literacy.
- Lack of support from executives. A data-driven culture is much harder to achieve without support from the top levels of an organization. Company leaders should share information about the benefits with reticent executives.
Companies that excel at DDDM combine the critical factors of a robust data analytics solution, employees proficient at data interpretation, and a supportive culture. How can companies that don’t have these factors in place adopt them? It may not be an easy transition, but here are a few tips:
- Be ready for change. Before considering a data analytics solution, ensure the company is ready from a change management perspective. Are key executives on board? Are team members ready to shift their thinking to a DDDM approach? Are you prepared to train employees in proper data analysis skills?
- Explore all options. Before purchasing a data analytics solution, explore all the options, including the possibility of custom software development. Be sure you know the kinds of information you will want to gather as well as where that data will come from, given you probably already have numerous sources that could be consolidated.
- Teach data literacy. Ensure you have a training program in place to help employees become more data literate. This process is similar to previous decades in which employers had to train some workers in computer and internet literacy, which — like data literacy now — wasn’t widely taught in school.
- Build a DDDM culture. The right technology and team member abilities won’t go very far without a data-driven culture to support them. Build an internal DDDM messaging program and deploy it across all employee communications, including internal web resources, virtual workspaces, meetings, and plans for new initiatives.
How to Implement
Once you get past the limitations listed above and have the success factors mentioned in the previous section as a foundation, you can start to take the essential steps for successfully implementing DDDM:
- Identify company goals. For example, say you want to increase revenues by 15%. The more specific your goals can be, the easier it will be to know when you’ve reached them. If your goals are more amorphous, such as expanding reach with your marketing programs, identify data points, such as social media likes that you can use to track milestones.
- Determine data sources. Some data sources may already be available and require no new technology to gather. However, combining data sources is highly useful, and you may need additional tools and technologies to achieve it.
- Collect data. Gather data from your sources.
- Examine and analyze data. Using data analytics software, create dashboards that show you the information you need in a usable format, such as a report or graph. Ensure the solution you use enables you to dive down into more granular information and to compare from one week, month, quarter, or year to the next.
- Act on insights. Draw conclusions from your data analysis. For example, you may find that competitors are offering a product that you’re not, and you need a new piece of equipment in order to create it to drive up your revenue. Determine the best time to purchase the equipment and begin to develop and market the new product.
- Review progress. After a reasonable period, examine an updated report to find out if your actions have proven effective. Perhaps your revenues have increased by 5%. That’s progress toward your 15% goal!
Taking the Next Step
Business leaders must make decisions every day and the quality of those decisions has an enormous impact on company success. Different people like to go about decision-making in different ways, and there is certainly still room for intuition, hunches, and educated guesswork, especially because there are things no one can know for certain.
Still, when based on the right information, data-driven decisions are more likely to be successful, driving growth, increasing revenue and profit, and improving reputation. Many companies already have much of the data they need to help them make these highly informed decisions. The next step to make the most of it is to bring it into their everyday processes.