A highly skilled doctor recently contacted me. He struggled to understand why his newly established practice wasn’t meeting his financial expectations. He is a brilliant doctor but had never run a business before. He came to me to help identify why his business was not returning the revenue he had projected. To identify potential causes and fixes, I turned to data analytics.
Working together, we identified two key data points: dollars billed to insurance daily and the percentage of dollars collected vs. dollars billed. We found that both were under what was expected. Once armed with that understanding, we could ask pertinent questions like: How do we ensure paperwork is completed and sent to the insurance companies? Or, are we maximizing the collections vs. billing? Once these two areas are controlled, we will focus on expanding his business offerings.
Data analytics can bring a wealth of knowledge to any business leader. Like many other valuable tools, data analytics can be daunting. Data can be difficult to obtain, can require skills to decipher and may not provide an obvious course forward. Despite these challenges, unlocking data can be a turning point for an organization.
When discussing the value of data, I often use the example of flying an airplane. Pilots use their surroundings and instrumentation to provide the information needed to fly an airplane. One important skill for a pilot to master is flying only with instrumentation. This is critical in poor weather with low visibility. Without instrumentation, a flight in inclement weather could be cut tragically short.
Imagine flying an airplane based solely on the information you could gather by looking out the window. A skilled pilot, familiar with the aircraft and the local terrain, could likely pull this off, but many valuable data points would go unseen. For example, it becomes significantly more likely that a pilot will run short of fuel if they cannot see the fuel gauge. Simply put, pilots need to see accurate measurements to do their job properly.
Many business leaders find themselves in the same situation as an instrumentless pilot. They may have visibility to major guide points, like current sales or headcount, but they may miss significant opportunities for improvement, like production productivity or margin erosion. They may be able to see out of the airplane window, but they need to know their true bearing. Many leaders run their businesses as if looking out the window, with little visibility to the wealth of valuable guidance they could have. With full visibility to the instrument panel of their organization, a leader can make more informed decisions.
How to build a data-driven business
How does one start or improve their use of data in their business? Below is a brief framework for getting started.
Step 1: Identify what is important
If you have been in a field for many years, you may already know what information will help you drive good business decisions. If you are just starting and don’t know what you are looking for, you may need help. My doctor friend is the perfect example of this principle. He did not know where to start. We began by identifying the problem. In this case, it was cash flow. We then began to follow the money. His review was simple. This may not be the case in every situation. In my experience, the more data you can review, the better hold you have on your organization and the better decisions you will make.
Step 2: Find the data
To analyze data, you often need to know where to find it. This can be a challenge; many times, it is not readily available. For my doctor friend, the data was in his billing software, but that may not always be the case. In one factory I led, we had a department with very inconsistent output. Four employees were doing the same job, but some days, our output would be twice what was expected. Other times, the production seemed completely stalled. Since our Enterprise Resource Planning (ERP) did not track employee production information, I began using a spreadsheet to track the department’s production each day. I simply gathered the worker’s name, the part number and the quantity produced of that part. With this data, I saw what was happening in the shop — two employees did 75 percent of the work. I learned how many of each part we could make daily, and we generated production cycle times from this. This information drove both resource and production planning, which led to good management choices and increased productivity and profitability. Fixing this problem also led to a 30 percent increase in output of the whole plant because we alleviated the No. 1 bottleneck.
Typically, a company uses a data collection system in the form of either financial software (like QuickBooks) or ERP software (like SAP). These systems are great resources if you know how to extract the data. Companies need an individual or a team that can assist in creating reports and extracting data from an ERP. If not, you may need to collect data manually in a spreadsheet or hire an outside body to help you benefit from your system.
Step 3: Prepare your data
Once you have raw data, you need to know what you are looking at. This can be very challenging. Often, there are bits of what I will call inclusions that, just like in a diamond, can reduce the value of your data. For example, if you need to know your product’s average sales price and have given away a number of that product as samples, you may or may not want to include those zero-dollar data points in your data set. The decision to include the data depends on your goal for the information. You will often want to limit the information as well. At some point, data from the past lose relevance and can skew your results in a misleading direction. Data scientists spend years honing their ability to filter, sort and exclude irrelevant information. The more you know about your data and the more you prepare it, the more value it can generate.
Step 4: Tell the story
Once gathered and sorted, data needs to be presented in a way that allows for good decision making. As a supply chain and operations leader, I use data to look for trends. These trends have included information like the average unit sales and the number of calls received per customer service member. Looking at trends, a leader can know how to address problems before they begin. By reviewing these trends with functional leadership in middle management, you can show leaders what is happening in their departments and decide the best ways to react. Years ago, when my responsibilities included overseeing a customer service team, we reviewed average calls received, average orders written, time on the phone, etc. When our staffing needs changed, it was never a surprise. We already knew what was happening in that department and could easily scale up or down based on the needs we extrapolated from the data.
Step 5: Consistently review
The final key to good data management is consistency. Returning to our doctor friend: Regular reviews of critical billing steps allow the practice to see if it is successfully managing the business side of its operations. Without this visibility, the team cannot measure what has been successful and what has not. They might continue to leave money in the hands of insurance companies without realizing it.
Data should be reviewed regularly at appropriate intervals — hourly, daily, monthly or quarterly, depending on the need. In most cases, I recommend monthly reviews involving all affected management. This has a threefold benefit.
Vision: When management can see what is happening in the company, they can understand the root causes of organizational challenges. This helps everyone see solutions and builds buy-in when things change.
Input: When multiple managers are involved and understand what is happening in the company, they can provide solutions to these issues. As a leader, I am a firm believer that I do not have all the answers, nor do I always have the best answers. If the whole team can see the challenges and present thoughtful solutions, an organization can multiply the value of each employee.
Accountability: We all want to know that our efforts are seen and appreciated. When progress is on display for all to see and bosses praise success in front of colleagues, most leaders are motivated to offer their loyalty and best efforts.
Data can be tricky. There are whole organizations that provide data-analysis services. Data analytics is not just a tool but a critical skill that can transform your business. Just as a pilot uses visual cues and instruments to navigate, leaders can leverage data to gain a complete understanding of their operations. By identifying key metrics, sourcing reliable data, preparing data and consistently reviewing it, companies can find new opportunities and make informed decisions. It may be challenging, but the rewards are well worth the effort.