3 Keys to Becoming a More Data-Driven Organization

Tractor Zoom recently had the opportunity to exhibit at John Deere’s user group meeting in Las Vegas. Data, and how it is used within dealerships, was the feature attraction. As exhibitors, we were able to lead a class on helping dealerships become more data-driven in their decision making. On stage our TJ Masker, VP of Product Development, was joined by Brian Knotts, COO of Koenig Equipment, in sharing their experiences helping dealerships shift their traditional decision-making processes with a more data-first approach. The following post is a summary of that class. 

It should be no secret that basing your decisions on factual information produces better results. Logic implies that if your entire organization makes decisions based on solid data, then even more positive results abound. Benefits to this way of decision-making include: 

If it was easy though, we’d all be doing it. Some of the most common challenges include: 

These roadblocks can be condensed into three main actionable challenges: Culture, Time Horizon, and Data Quality. 

Culture, according to the NewVantage Executive Survey, is the biggest impediment around data initiatives for the fifth straight year.  According to Brian, an essential ingredient for a data-driven culture is formal adoption by the C-suite leaders. It must be a regular focus of meetings, communication, and the way they operate. From there, kick-off meetings, signage, and all forms of communication need to reinforce what you are promoting. Koenig also focuses on five key metrics that drive their business. Brian emphasized the importance of five, or fewer, KPIs. This way employees can easily identify those drivers that then enable them to make impactful decisions without losing sight of the main goals. 

At Tractor Zoom, we’ve seen organizations adopt a more data-driven approach as the user experience becomes less complex and more compatible with their existing day-to-day process. Through the evolution of Tractor Zoom Pro, we have made changes that have reduced redundant steps for users, and in return, has driven up efficient uses of the platform. Two recent examples of this are the Anvil CRM integration and automatic email notifications when dealers’ inventory is priced outside their acceptable market ranges. 

Organizations looking to adopt a stronger data-driven culture can benefit greatly from a short-term win, but also necessitate a long-term commitment in order to make lasting change.  Having a short-term, ideally ROI-driven project, which you can more easily execute and celebrate the win is likely to build the momentum and support needed to get other stakeholders on board. TJ provided the example of Atlantic Tractor working with Tractor Zoom to improve their inventory repricing strategy. In six short months, their growing dealership was able to improve used margins and reduce their risk of aged equipment. All of this without needing to add additional headcount. Significant wins like this have helped convince others of the power of data-driven decision-making.  

Brian added that hiring a non-revenue generating person is a strong commitment to long-term results, but it also can help aid in short-term gains. Koenig has added a data analyst to their staff, who we communicate with regularly. While the gains this person will provide are not expected in year one, they have already started to make a positive impact to the bottom line across the organization. 

Garbage In. Garbage Out. It is almost cliché by now, but none-the-less truthful. With so much data being collected today, many organizations, dealerships included, can quickly be overwhelmed. Here, both Brian and TJ mentioned the importance of good, trusted partnerships to help you collect, clean, organize and make the most of your information. Brian went on to elaborate that the partner should not just be transactional, but rather have a clear path for their, and your, continuous improvement. 

At Tractor Zoom, TJ states, there is nothing more important to us than quality. That is why we have built three layers of protection to help ensure data quality.  The first is the direct partnership with auctioneers and dealers to help ensure good data is received. Second, we have a quality assurance team in-house who is responsible for reviewing and ingesting all new data daily. Finally, through data science we have built an outlier detection model to identify lots with values outside of expected parameters. 

With the right kind of quality data, along with a culture and plan to base decisions on that data, Brian believes dealerships will be able to thrive, not just survive, during the industry troughs.