People, not just products
With such a big product portfolio in the data analytics space, it’s easy to forget about human capital. But the role of people in IBM’s Big Data initiatives arguably eclipse the products in importance. To start with, IBM has a huge research faculty, including what Advani told me is the largest mathematics department in private industry. This clearly provides significant firepower in predictive analytics innovation.
And then there’s IBM’s acquisition of PriceWaterhouseCoopers’ consulting division back in 2002. Even prior to that deal, IBM had a substantial global services division, but the acquisition of PwC Consulting transformed Armonk from a products company with a services organization to, arguably, a services organization that leverages an impressive array of its parent company’s own products.
Advani introduced to me another of IBM’s analytics initiatives, called Analytical Decision Management, which focuses on embedding analytics functionality within business applications, rather than forcing frontline workers to go into dedicated, siloed analytics apps to get those insights. This initiative allows, for example, call center workers to understand what offers are appropriate to certain callers and what outcomes are likely when the offers are made. Users of these applications don’t even sense that they are using analytics technology, because it’s embedded into operational workflows. Clearly, IBM’s combination of research and services delivery experience enhances its ability to deliver in such frontline worker scenarios.
My conversation with Advani was indeed eye-opening. I’ve been watching IBM build products and buy companies for years, and I’ve understood its interest in Big Data and analytics. I just hadn’t put it all together in my head. IBM is in a unique position, and doing things in the Big Data world that its competitors cannot.
It’s not easy being (Big) Blue
But this observation is a bit humbling as well. How will other tech companies, especially startups, hope to build out a similar data analytics empire? And how will IBM manage so many different products, technologies, consulting teams and acquired companies? After all, most big empires eventually fall into decline.
It seems to me that IBM will need to integrate its product portfolio as the new versions of the products are released. On the BI side, I’ve seen that start to happen, and it will need to continue. Meanwhile, small startups, unencumbered by the management of so many moving parts, are critical for launching and propelling innovative technology, and the markets around them. Big Data is proof of that.
Ultimately though, things will need to converge. The Big Data space will mature, more Enterprise software companies will enter it, they’ll acquire some of the startups, and consolidation will occur. The startups show us the importance of idealism and breaking new ground. IBM’s position shows us the importance of connecting Big Data with the Enterprise and a mainstream services organization. It also demonstrates the power of embedding analytics functionality into line-of-business software that may deceptively register as mundane.
Cutting edge innovation is critical, but its full value is realized with integration into mainstream tools, products and companies.