As AI and machine learning become more prevalent, businesses are exploring ways to improve decision-making processes using data.
These explorations vary from company to company. An online retailer could use data to determine where customers are falling off during the customer journey. A bank might use data to anticipate refinancing timelines and triggers.
Regardless of the industry, the idea that the numbers don’t lie rings true. Here are seven tips for implementing data-driven decision-making in business.
Audit Gaps and Set Goals
To make effective changes in your business, you have to look back before looking forward. When it comes to success with data, auditing gaps will help highlight priorities and resource needs to accomplish your goals.
Take this time to determine what decisions have failed in the past, where data access is lacking, and what questions you want to answer. Then, set strategic goals for what you hope to achieve with this data and success metrics to quantify your progress.
Put the Right Tools in Place
Once you have a clear picture of what data you need to collect, the next step is determining how to collect it. Improving data collection often requires investing in relevant ETL tools— Extract, Transform, Load—to turn relevant data into useful information.
At this point, it’s time to look at bringing in a strong data science specialist or team to lead the process.
Create a Cultural Shift
Moving to a data-driven decision-making process entails a mindset shift toward the analytical. When disrupting the status quo within your business, that means looking at a top-down cultural shift as well. Getting buy-in at the C-suite level and creating a precedent for data-driven decision-making is integral for success.
At this juncture, it’s beneficial to invest in training and education to improve employee buy-in. Programs like Lean Six Sigma train key decision-makers to improve processes by focusing on statistical analysis. Implementing this level of training will help spark the cultural shift toward data-driven decision-making.
Break Down Barriers
Creating a data-driven enterprise will never succeed if your business operates in silos. Big data transcends departmental (and cubicle) walls to highlight the interconnectivity between business functions and processes.
Ensure that everyone has access to data and to each other. Having one team access and analyze data guarantees that they’ll find information that’s seemingly irrelevant to them but could be revolutionary to someone else. Provide opportunities for data scientists to work with different teams and groups to understand unique challenges and needs. Rather than focusing on leadership, empower employees at all levels to speak up.
Improve Communication Skills
How you convey data to someone is almost as important as the data itself. It’s integral to find ways to share information in an accessible, engaging manner. Visual representations of data like pie charts and bar graphs may seem outdated, but they’re simple and easy to process at all levels.
Verbally relating the information is another worthwhile focal point. Don’t just spit out numbers at people; tell them how it will change the business and impact your employees’ experience.
Don’t Discount Intuition and Experience
There’s a common misconception that shifting to a data-driven process means eliminating intuition and the human experience from the equation. While data-driven decision-making does shift the focus to numbers and analytics, the most successful businesses make space for humanity.
Consider correlation and causation in statistics. Sure, the numbers don’t lie, but sometimes they miss mitigating factors and make two occurrences look related when they are not.
Scientists once believed that ice cream consumption caused polio, when in fact, hotter summer temperatures created an ideal environment for the virus to thrive. Summer heat caused an increase in ice cream consumption and polio transmission, but the two are otherwise unrelated. It took human experience and knowledge to understand that.
Making data-driven decisions means putting the numbers together so a human can decide the best path forward with that information.
Create Implementation Strategies
Putting the right tools in place and creating a data-driven culture is a monumental process. For many businesses, there’s an anticlimactic “now what?” when that portion of the work is done.
Take the data you find and create implementation strategies, following the same process of setting goals and success metrics.
You now know that customers in your online store seem to bounce during the transaction process, which seems to be running slow. How will you change that?
Your bank now knows that homeowners tend to refinance after they’ve built up 15 years of equity. How will you market a favorable, profitable solution to them in anticipation of that event.
Making data-driven decisions is just the first step. Executing those decisions is what leads to long-term success.
