More than six years ago I was actively researching my third book The New Small. The text explores many common themes among 11 small-business owners adopting emerging technologies. Perhaps my favorite was the “all-hands-on-deck” mind-set that permeated the group. Without exception, each individual displayed an astonishing degree of pragmatism. They understood that traditional job titles often didn’t correlate to their daily roles and responsibilities.
Of course, that’s not true across the board. Few employees in large or mid-sized organizations can routinely get away with like bulls in a china shop. Employees who fail to observe proper protocols run the risk of breaking things, ticking off colleagues and superiors, and causing audit and regulatory issues. Sure, we know that HR processes new-hire paperwork and AP cuts vendor checks. Yet sometimes responsibilities aren’t nearly so clearly define. As a result, things sometimes get muddy.
Who should be responsible for analytics?
Case in point: analytics. To be sure, there’s no one way to “do” them. I can think of several models that successful companies use:
- A traditional center of excellence (CoE)
- A completely decentralized approach
- Splitting employee expertise, often via a chargeback method
- Outsourcing analytics expertise to third-parties on an as-needed basis
- Seeking ongoing support from consulting firms
- Hybrid approaches
I can’t condemn any of the above methods as completely inappropriate. Some companies find logic in option number five: outsourcing, even on a permanent basis. For others, though, it might not make as much sense. Much like strategy, isn’t developing in-house expertise a critical business goal? What happens if that trusted third party goes away? What to do if it begins working with the competition? And what about privacy and security concerns?
To be sure, there’s no one way to “do” analytics.
I can think of several high-profile organizations that have outsourced their analytics needs on a regular basis. In each case, the problem didn’t solely stem from a lack of internal expertise (read: employee skills). No, they simply didn’t possess the technical capacity to store and analyze new and increasingly “untraditional” data sources. Put differently, their business needs changed and their IT support couldn’t keep up—at least as fast as its marketing and sales folks needed. Along these lines, Chris Nerney’s writes:
Without the right IT infrastructure in place…data initiatives can fail to deliver the benefits anticipated by enterprise decision-makers. [C]ompanies can’t reap the full benefits of their analytics efforts unless their technology organization is up to the challenge of managing the data that makes it possible.
Good point. I can’t help but think of Conway’s Law.
Simon Says: You can’t fault execs for looking elsewhere if IT can’t meet business needs.
It’s downright silly to ponder which departments, groups, and individuals should be responsible for analytics in isolation. After all, there are many different factors at play. At a high level, it may be ideal for organizations to handle its own analytics, but it’s hard to fault CMOs and their ilk for looking at external alternatives these days. Consider the following questions:
- What happens if other IT priorities routinely take precedence?
- What if IT budget cuts result in delays to the technologies supporting key analytics efforts?
Brass tacks: If IT departments cannot meet analytics needs, don’t be surprised if CXOs respond by looking outside the organization.
What say you?
I’ll come back to this idea in my next post.
IBM sponsored this post.