Organizations must find the right balance between tactical use of their data and strategic use of their data. The following statement encapsulates the difference between an application that was primarily designed from a tactical perspective versus a strategic one.:
"Thanks, you delivered what I asked for (tactical), but not what I wanted (strategic)."
If you are in IT, have you ever heard this statement from the business side of your organization?
If you are in business, have you ever said this about a new business application/solution?
This type of statement points out an information-related pain that exists in many organizations. It is the result of using a more tactical design process, which is the premise used in building the majority of applications. To understand this a bit more we must first describe the basics on which any application operates. An application needs to access data, process this data into information, and deliver this information to decision makers (all in a timely manner of course).
A business user asks for an application to help provide insightful information that will be used to improve or grow their organization. The IT department hears the request for the delivery of a SPECIFIC insight which has already been discovered (that is part of the problem). IT did not understand that the business is really asking for an application that can help deliver new insights NOT just a specific one that has already been discovered. Business doesn't help here either because they are not able to explain exactly all the insights they want because no one has discovered them yet. Regardless, IT now has a specific end point or deliverable in mind and sets out designing an application based on the data currently on hand that will deliver a specific outcome over and over again. This is an example of using a data centric or tactical approach in your overall design process for a business application.
A strategic approach should be used to drive the overall design process because it ends up providing more value in the long run. It should be designed on providing business users a way to discover NEW insights on any data that is available now and in the future. This allows for a more agile way of delivering different insights as they are discovered while at the same time continuing to deliver all the specifically defined "known" insights that still provide value. This is a more strategic way to design and use data and is based more on using analytics to drive the overall design process instead of just the data. This type of design also saves IT resources. One simple example of how IT resources can be saved is by having an application that allows drill paths or hierarchies to be defined on the fly instead of OLAP cubes needing to be created and maintained over and over again.
Which design process do you think is easier to implement?
Which design process do you think provides more value?
SAS Visual Analytics is just one of our high-performance analytics offerings which serves as a great example of a flexible business application based on using analytics to drive the overall design process which empowers information sharing and insight discovery.
Learn more about "big data" and high-performance analytics in this special 32-page report on high-performance analytics.
