Hey, it's complicated!

Reading the most recent blog post by James Kobielus, my mind is spinning from the array of options that you might want to use to differentiate on Analytics. And, as James aptly points out. none of these technologies are designed for use by the masses, let alone executives.

With analytics technology spend increasingly being spread out to the "masses" (departments, even end users), how can you get projects off the ground? It seems to me:

• Start big, or start small, but don't start in the middle. Presenting a radical transformation can get you in the door with executives. From there, you might scale down to a piece of the puzzle that's practical to implement. Or, you can find a small, high-value problem with a defined solution for a quick win. From there expand into other advanced analytics areas (land and expand isn't dead). But going somewhere in between seems too complex for the return -- keep your big vision big, or your small project in scope until the deal is won.
• Know your customer. And I mean really know your customer, and everything they do. This is a little more than perusing the website and listing to the earnings calls. Understand their industry, culture, vision, and competitors. That business context is the only way to sell something this complex.
• Dig in for a long ride. These technologies aren't getting simpler. While there's potentially massive value to be had, it will take time, as will your sales cycles.

Coming off IBM's IOD conference, I've been trying to figure out how to position the breadth of the platform so that our partners (ISVs, SaaS companies, BPOs or consulting firms) can build product strategy around the next wave of analytic applications. The potential value of these applications is a hot topic, but how can we capitalize on it? While the breadth of the IBM platform is unmatched, it's tough to figure out where to start.

So, here we go. Use the Analytic Applications Quadrant below in your product strategy sessions, with your investors, or even your clients. And, of course, work with your IBM team to define and build your solutions across these different domains. Leave a comment, or shoot me an email with your thoughts...

X-Axis: Customer Awareness

The x axis of customer awareness is an indication of how much your customers have heard about these particular solutions. It's largely a factor of industry trends and marketing, media coverage, and focus by major technology providers, including IBM.

Y-Axis: Market Expectation

The y axis of market expectation measures the expectation that your solution(s) include the analytics categories. It's generally an indication of the maturity and adoption of the category in the enterprise.

The categorical representation breaks down as follows:

Core Functionality

Solutions that are generally expected to be delivered as part of your solution. They represent technologies that are generally pervasive in the enterprise across most, if not all, domains and industries.

While there may be business models that monetize solutions in this category, we believe the majority of solutions will be incorporated "out-of-the-box" in business software with no additional line item cost or surcharge.

Thought Leadership

These solutions generally have maturity in specific domains or industries, but have the potential to be applied more broadly. Customer awareness may be limited outside specific business units, but there are identified applications that improve business processes or user experience.

A common example is scenario planning. While planning using advanced technologies has been standard practice in Finance for many years, there are many identified applications for the technology outside financial processes that improve business decisions.

The business potential of these application is mixed. It may be a small component of an application or business process. In some cases, it may represent a potential up charge or micro application that can be sold.

Point Solutions

These analytic technologies satisfy specific use cases or industries. They haven't proven to have general applicability, but can be critical for certain business processes. As a result, these solutions can generally be sold to solve a specific problem.

A common example would be operational monitoring in a call center application measuring call volumes and wait times.

Strategic Differentiation

The next wave of widely deployed analytic applications will likely include these technologies, and they will give your products and your firm measurable ROI. While these solutions have substantial media attention and marketing from leading technology companies, their practical implementations are still small in number at the enterprise level -- they represent substantial opportunity for your company to build high margin businesses.