I enjoyed reading this post by Dave Kellogg on SaaS, which summarizes a really nice BVP piece. I took particular note of axiom #8:
"Leverage and monetize the data asset. You can do this by leveraging your expertise to identify the metrics and dashboards of most analytic value and further by then selling industry benchmark data on them. This, to me, is one of the more obvious SaaS opportunities, yet nevertheless to-date, in my experience, one of the most unexploited. I expect to see much more progress in this area in the coming few years."
Having spent a good amount of time over the past year working on this, I know it's a great opportunity, but it's not a simple problem to solve. If you're going to tackle it, take note:
- Build your application vision first. Make no mistake, treating this as an application (as opposed to a data feed) frees your mind from worrying about the technical challenge, which will come later. Get on a whiteboard, sketch on a napkin, gather around the campfire in order to...
- Define some good metrics. It's an analytical application at its core, which revolves around measurements, dimensions, and comparisons thereof.
- Broaden your technical horizons. To pull it off, you'll likely need several components or tools, including Database, ETL, Statistical Programming, Business Intelligence, and UI and Data Discovery Frameworks. Each adds value at each step in the data lifecycle, but also must be carefully orchestrated. Software advancements in most of these domains are scorching right now. That's great news for developers, but also requires diligent oversight to make sure everything works together. I've listed some of the important ones below, linking to IBM pages with more detail.
In most ways, these concepts aren't new. Data providers have been turning aggregated metrics into commercial assets for decades. But the explosion of SaaS combined with new technical advancements are creating new opportunities for insight into processes and metrics that, until now, were confined to the walls of individual companies.
IBM Links
