In
my last post I talked about our analyst conference in Spain and what messages resonated with them. We talked about analytics and how they can help our customers in the downturn. We also talked about making those advantages more accessible through software as a service.
It's part of a larger theme I've been thinking about: what analytics are and what they are not, in terms of being able to predict the future of your business. Let's be honest, analytics is in danger of becoming an overused and abused term, in the same way that “business intelligence” got watered down as more and more companies claimed to offer it.
It's no surprise I think analytics play a key role in helping companies make better decisions, especially now, when it can make a real difference in a tough competitive environment. A lot of companies might be worried about the cost, but cloud computing makes it more affordable for companies that need it right now but can’t afford to bring it on site.
We have to recognize that our customers are at different stages of their evolution. Employing analytics in a software as a service environment lets you see if they have a positive effect on the bottom line. If so, you can go forward with a fuller installation.
I stole this “
8 levels of analytics” chart from sascom magazine and use it in presentations. The first four levels, while they are legitimate and relatively commoditized at this point, don’t really show you what’s likely to happen in the future. They support reactive decision making. They’re great at benchmarking, but what about the other four types of analytics? If we think about growing our business in tough economic times, we need to be more proactive in our decision making. Steps 5 through 8 are all about the future: customers, suppliers, sales.
Again, this is where the term “analytics” has been watered down. There’s no doubt that everybody offers reactive capabilities, in spreadsheets, in OLAP cubes, in report writers. But how many people are using the proactive tools around optimization, modeling and forecasting? There’s a misconception that those capabilities are reserved for companies with massive computing power and PhD statisticians. That’s no longer true with the advent of cloud computing and software as a service.
That message appeals, not only to the analysts but to our customers.