How Data Driven Businesses Stay Ahead of their Competitors
Now more than ever it’s important for companies to stay ahead of their competitors.
As a data-driven business, you can do this by studying trends in your industry, observing trends in other industries, and most importantly, leveraging the data at your disposal.
We’ll provide an overview of helpful data points and how you—as a data driven business—can make actionable decisions based on them.
What kind of data is best for data-driven companies to collect?
It’s important to take a holistic approach to collecting data. Understanding primary and secondary data—qualitative and quantitative—will help you understand if you should pivot or continue.
Internal data helps companies understand the culture of the organization and how people are performing. Strong leaders at every level are needed. Strategic change happens at the top, but implementing those changes happens at the local level. All of this is necessary to enact the vision, implement strategic change, and stay ahead of your competitors.
Most companies have access to data in four categories:
Within those categories, there are three types that build on one another:
Descriptive data: This provides you with the “what happened?” information from your starting point to where you currently are. You can find this type of data in your balance sheet, profit and loss statement, productivity reports, and GDP numbers.
Prescriptive data: This data identifies the issues and tells you what you need to do.
Predictive data: This is the most powerful type of data because it predicts how customers will behave in the future. Also called attribution models in marketing or regression modeling in statistics, this data provides important information to which you can adapt. Not all companies use this data... but the best ones—the data driven businesses—do.
How should I track this data?
Make sure you have quality data first. Once quality data is in place, then you can implement dashboarding to visually track, analyze, and review your key performance indicators, metrics, and other data points. This allows you to syndicate organization-wide data and make it accessible for everyone. You will need to see strong data in revenue, financial information, and employee/customer retention in order for growth to happen.
How should I digest this data, and how often should I be reviewing it?
The frequency of data analysis depends on the type of data it is. Secondary analysis should be done once a year (or every two years depending on the industry) because things don’t change that quickly. Financial data, on the other hand, should be reviewed quarterly. Customer data, specifically in transactional businesses like retail, should be reviewed quarterly also. Employee engagement data should be reviewed every 6-18 months, depending on the company and the specific issues you are targeting.
Data is not a one-way street, so be sure to thank the customers and employees who provided it for you. It’s also not the be-all-end-all, but rather, a means of improvement. Don’t let it go to waste. Use it to make the following decisions:
Strategic change: Cross-functional teams sponsored by leadership are the ones who review the data. They have the authority to do something about it and make changes based on statistical significance.
Tactical account level change: Account managers make real-time, data-driven adjustments that improve business and increase profit margins. Responsiveness is the priority. Taking data and turning it into something beneficial to the customer or employee shows that you’re listening and that you value their feedback.
What should I do with what I’ve learned?
Transparency of the data is important, and the executive team must be willing to hear the good, the bad, and the ugly and do something with it. It must be shared with other leaders and departments in the organization so everyone feels invested and works together to implement change.
As a general trend, data analysts sometimes think their organization is performing better than the data indicates. For example, an employee who helps a customer, but receives a mediocre review, might reject the data as not being accurate. This belief can impede their efforts to predict customer behavior. It’s important to educate the employee that the data is not “self-evident.” Connect the dots and empower them to trust the data.
Continue to nurture your partnership with the front lines by soliciting their feedback. They are the ones who implement change, and incorporating their insights will give them greater ownership over the process.
In the midst of the COVID-19 new normal, data is a great way to discover what your employees and customers need—and what your business might look like in the future.
Data analysts like to say, “Past performance is not the predictor of future performance.” It’s hard to change something that’s been done the same way for 30 years. However, you have to listen to the data. Combining your experience with your data can make a powerful impact. You will successfully become a data-driven business that performs ahead of your competitors.
Do you need help analyzing the data for your business? Connect with us here!