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Thursday, December 09, 2010 - How well does your data drive your decision making? Three elements for continuous improvement
by Dr. Shannon Flumerfelt


During a recent vacation, I was in a tourist area and noticed a sign at a local restaurant establishment. The sign read, “Order Your Cajun Fried Turkeys Here,” followed by the local phone number, minus the area code. As a tourist, I was not familiar with the area code; so at the time, I wondered what it was.

In other words, if I was interested in ordering one of these southern culinary treats and if I was not familiar with the area code for this restaurant, this lack of real time information might be enough to sway me away from ordering the Cajun fried turkey in the moment I was ready to do so. In considering this simple omission, not posting the area code with the phone number, I thought about the gap created by this one key piece of information. This gap of data represented a key disconnection between all of the work that this business owner had gone through to make this product available and the product being easily accessible to customers.

It is likely that the owner had to complete several process steps, such as mastering the frying technique, establishing the Cajun spice recipe, finding a turkey supplier, training employees to prepare the turkey, creating a protocol for taking orders and obtaining packaging for customer pickup. The process steps were undoubtedly designed to sell as many turkeys as possible during the peak season to tourists. The lack of critical data to help the customer drive to the decision to purchase is quite a blunder in the light of everything else the owner most likely did well.

In putting up this sign, the owner should have simply considered the customer’s view. The customer’s perspective is the foundation for any activity associated with Lean data-driven decision making. This includes three elements considered from the customer’s view: data that are important (such as the area code), timely (such as during tourist season) and sufficient (such as the area code, but not the zip code).

The Three Elements for Data Driven Decision Making and Continuous Improvement
In the eyes of the customer, is the data:

1. Important?
2. Timely?
3. Sufficient?

Whether data drive external customer decision making or internal decision making, they should always enhance what matters to the customer in the end. When all three elements are engaged, data that is important, timely and sufficient to the customer, then data-driven decision making can drive improvement. Let’s consider two scenarios typically faced by schools in regard to relating continuous improvement and data driven decision making and these three elements.

A colleague of mine, an administrator in a school, recently commented how much data collection and analysis has changed in recent years in the educational sector. So, let’s look at a scenario reminiscent of what schools faced just a few short years ago, when teachers in classrooms felt a lot like I had as I considered whether or not to buy the Cajun fried turkey. I knew that there was an area code that I needed, but I did not have access to it.

In the same way, teachers knew that there were student data collected regularly through various standardized testing programs, but they did not have access to it when they needed it to make instructional classroom decisions. Likewise, building and district administrators were in the same position, as there were data on student achievement that they needed for district decisions, but they did not have access to it when they needed it. Hence, teachers designed and taught lessons, and administrators built and administered budgets and instructional support, but they did not have the data needed to drive decisions for improvement in a timely way.

Under these circumstances, two of the three elements for data-driven decision making were met: having important and sufficient data. Unfortunately, the remaining element, timely access to data was not met. In response, many districts have worked to overcome the barriers to timely access.

In contrast, a second scenario highlights how schools do have more timely access to data than ever before. In fact, data collection, analysis and dissemination systems are quite good, with various vendor product/service packages rolled out, as well as internal and regional service agency data service support being widely available. The data available to both teachers and administrators are provided in real time or with very fast processing speeds.

Yet, there is something interesting happening under this scenario. Where districts previously dealt with a dearth of data due to a lack of timely access, they are now inundated with data, resulting in a lack of identifying important and sufficient data. Districts have so much data that they have difficulty sorting and prioritizing it all. Hence, in enhancing one element of data-driven decision making, timely access to data, schools might be losing two other elements: important data and sufficient data.

These districts with enhanced abilities to generate timely data lack identification of important data because there is a need for shared organizational intelligence about which data are important. These districts also lack sufficient data because they have overproduced data.

Under this second scenario, administrators speak of watching piles of data accumulate and teachers describe being overwhelmed with data. Hence, the ability to use improved data to drive improved decisions is equally as dysfunctional in both scenarios – in the first scenario when there were no standards for timely data or in this second scenario where there is no sense of what are important and sufficient data.

So, where does a school district make adjustments to data-driven decision making efforts when any one of these three elements is missing? By beginning with a simple question, “What data is important, timely and sufficient for our stakeholders?” Asking and answering these three questions in a collaborative manner will provide great clarity and enhance data-driven decision making greatly.

Data-driven decision making should be directional and deliberate, based on a shared understanding of the stakeholder or customer of most importance for the process under consideration. When that stakeholder is identified and the three elements of data-driven decision making are fully employed, then the continuous improvement process is engaged.

So, don’t hesitate to find out what data matters to your stakeholder; focus on data that is important. Don’t forget to activate data when it is needed by a stakeholder; provide timely access to it. Don’t be afraid to push aside data that does not matter to your customer; focus on data that is sufficient. And then enjoy the benefits of using the three elements that make data-driven decision making for continuous improvement work. By the way, if anyone knows of a good place for Cajun fried turkey, let me know. I never did find that area code!

 How to Begin to Engage in Continuous Improvement?
Answer your questions about data from the stakeholder’s view:

-Which data are important to our stakeholders?
-What is required for timely data access by our stakeholders?
-What is sufficient data for our stakeholders?
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