🐣 This Week I Learned -- The Power of Structured Data
In today's data-driven world, organizations are collecting vast amounts of information from various sources. However, the true value of data lies not in its quantity, but in its quality. It can be a significant challenge for a small business to invest the necessary time and resources to build high quality data assets which are necessary for facilitating future growth. What are the attributes of high quality data assets? The data you are gathering must be:
Accurate
Consistent
Relevant
Timely
Documented
Accessible
This is the basis for what will allow you to make informed decisions on your business. It’s also much easier said than done and something we have seen even large, sophisticated businesses struggle with because it often requires discipline across an entire organization.
A valuable data asset does not need to be complicated, in fact, simplicity is often better. One data asset we’ve been working on improving with the team at Stokes Counseling has been our waitlist. Today the waitlist is updated manually by our admin team (yes, we would prefer to automate this process, but that is a post for another day.) The waitlist is a really important tool for us because our goal is to schedule the best potential clinician match given schedule and capacity constraints as expeditiously as possible. The number of potential patients on the waitlist can be well over 100 at even given time so keeping track of the waitlist is a significant task and can become unwieldy if you’re not careful. Below is a screenshot of the waitlist which is currently tracked in a Google Sheet.
While the team does a great job managing the waitlist and ensuring the best fit for our patients, the data lacks a consistent structure that would allow us to analyze the data effectively. Let’s look at the data again to see why.
See the lack of consistency for days of the week and time? Similarly there are inconsistencies for location and gender preference. That may not seem like a big deal but it makes it extremely challenging to sort the data or write formulas to answer questions we might have like — what hours of the day see the highest demand? Do more patients want to be seen in Naugatuck or Ansonia? Or and even more difficult question such as how many patients have a preference for a female clinician in Ansonia on weekday evenings? To answer those questions today would be an arduous process to cull through our list and manually count each individual who mets the criteria. Yet, being able to answer such a question would help us prioritize our recruiting efforts to meet the demand of our patients and ensure they receive access to care in a more timely fashion. In short, it means we can be more effective in driving our growth.
You can certainly use Google Sheets or Excel to create the structured data framework, but I chose to use a free version of Airtable for two reasons — 1) I wanted be able to make use of a multi-select option for inputting data (see Availability column below) and 2) Airtable allows me to create saved views that could assist our admin team when scheduling. For instance a view the shows which patients would like to be seen in Naugatuck after 4pm simplifies the scheduling task if clinician availability opens up for that place and time.
We can also automatically see the results of how many patients we have on the waitlist by location so we can better understand and address a supply / demand imbalance.
Regardless of your database of choice the most important thing is to create a table that is well organized and consistently labeled so that it can easily be processed by analytics tools so you can uncover patterns and trends that would be difficult to identify manually. By prioritizing data quality and investing in structured data best practices, SMBs can unlock valuable insights and make data-driven decisions to drive their future growth.