In many situations, NoSQL platforms and multi-structured data sets are looking for use cases to solve. How many have heard the following?

Using sensor data will solve quality struggles in manufacturing.

Multi-structured social data is THE answer to revenue issues in retailing.

Accessing documents will be the answer to patient problems in healthcare.

Many prognosticators and analysts have talked about the myriad of technical aspects that can be solved with NoSQL but many are missing the details on how exactly to make those predictions a reality. Often this reality requires matching a particular technology solution with a particular top or bottom line aspect of the income statement. The ability to increase revenues or decrease costs directly is usually the first and best uses of a technology. Looking at “technology history,” you see this many times.

In financial trading, every transaction has a revenue and a cost aspect. For many years, in-memory database and predictive analytics vendors have made marketing “hay” ( … and quite a bit of revenue) with these opportunities. Matching the speed requirements of traders with the information available in operational trading platforms was the key. Some even say that these platforms provide too much advantage ... 

In the airline industry, the two highest expenses are associated with fuel costs and labor in the form of pilots and flight attendants. Not insignificant when you think about the fact that a Boeing 777 costs anywhere between $260m and $315m a piece. For airlines, their ability to lower costs via flight operations and effective staffing is one of the largest drivers behind the fact that optimization algorithms have been used in the airline industry for over 20 years and are becoming more important as fuel costs continue to rise.

However, both of these industries are relatively mature and the analytical and operational opportunities for NoSQL platforms, while still available, are not as open as they might be in other less “robust” industries. This is where a moment in history might be presenting itself for NoSQL platforms … health care business models are going to change dramatically in the next couple of years, and there will be a shift in areas from where traditional hospital revenues are generated. Cost centers will also change.

One area that was highlighted recently is how patients who stop taking their long-term medications can cost the overall healthcare system an additional $289b in "extra" treatments and additional hospital stays. A Businessweek article talks about multiple technical operational solutions from mobile apps to wireless-enabled prescription bottles to sensors in pills to confirm they have been taken. No matter what the technical solution, each of these ideas is going to generate some form of data that can be used for the intended operational solution of promoting that patients take their medication. This information can also be used analytically to determine the best treatments for particular ailments. It will also show the best “assistance” models for particular patient groups. For example, senior citizens are one of the fastest growing groups for smart phone adoption. Mobile applications might have more impact on their proper intake of their medication than tracking with “lo-jacked” prescription bottles. Using mobile applications might cost less as well being more effective.

In any event, health care is going to provide many of the openings for NoSQL platforms that they might not have otherwise found in other industries such as financial services or transportation:

  • Greenfield opportunities for technology implementations
  • Large and high profile opportunities to lower costs (or replace revenues)
  • Diversity of data sources that will challenge the processing power and data structures of most SQL based solutions.

What say the readers?
Are we ready to have our pill intake monitored and managed? Can NoSQL platforms really tackle a $300b problem? Do NoSQL platforms and solutions want that level of visibility and scrutiny? Do they want to tackle greenfield technology operations?

Provide your comments below and/or ping me via Twitter at @JohnLMyers44 with the hashtag #noodlingNoSQL.