I now have had the opportunity to meet with many organizations who are intently interested in doing much more with big data analytics.
Like other big topics, there's an extremely broad range of proficiency levels and associated needs. That being said, I'm now starting to see some familiar buckets of situations and needs.
Read through this, and ask yourself -- where is your organization on this continuum?
To Start With
One of the more powerful themes in business thinking these days is the use of big data analytics to not only dramatically improve existing operations, but create entirely new opportunities.
One of the more persuasive proponents of this school of thought (Tom Davenport) has written several excellent books on the topic -- a good starting point for many.
Smart CEOs are getting interested. Smart CIOs are realizing that the CMO might be their new best friend. It's the new "corporate R&D".
But using big data analytics as a competitive weapon is not entirely a new discussion -- many businesses have been using data warehousing and BI software for years.
What's relatively new is the scale and intensity we're seeing. For some businesses, this is the new Mother Lode of new business value. Many are at the other end of the spectrum and wondering how to get started.
Everyone seems to be at their own stage in the journey. But there seem to be clear categories with similar needs and concerns.
Group 1 -- The "Data Professionals"
You don't have to go far to meet organizations that "get it", and have been that way for quite a while. The unique and compelling business value associated with analytics at scale is an article of faith -- you don't have to convince anyone of the business value.
Here, you'll always find a group of hard-core data scientists who are continually pushing the boundaries and delivering new insights. You'll also find senior executives who listen carefully to their insights, and use their intellectual outputs to guide business and strategy decisions.
Outside of the core group of data scientists, you'll find a broader cadre of people throughout the organization who are getting more adept at using real-time and historical data to steer the business, and are getting more and more proficient at analytical concepts in the process.
From a technology perspective, their agenda is starting to become more familiar.
More data, more scale, more processing power. Many more data sources, many more analytical and visualization tools. A strong preference for self-service environments vs. asking someone to run a query. All quite understandable.
If you probe a bit, you'll hear some emerging concerns. Driving analytical proficiency deeper and more broadly across the organization. Building new collaboration and workflow models around rich analytics. Starting to tackle the fearsome and concerning GRC issues that result anytime you mash up a whole pile of data from interesting sources. Maybe some better data protection …
Here at EMC, we're starting to focus -- and invest -- in some of these new, emerging needs from this elite group. But not everyone is here …
If time and circumstances permit, I always ask "how did you get to where you are?". If you think about it, no one starts out being extremely proficient at big data analytics, building a cadre of data scientists, etc. It's an organizational capability that takes sustained time and effort to create.
There's clearly a journey involved. More on that later ...
Group 2 -- The "Data Hobbyists"
Behind this very visible and outspoken group, there's a much larger group of people who could greatly benefit from big data analytics, but aren't really organized for success.
For starters, there's not a visible core of hard core data scientists. Maybe there's an analytics junkie here or there, but the skill set isn't acknowledge as a critical core competency for organizational success.
As a result, the IT environment looks depressingly familiar. Multiple data sources and data warehouses, but no generic capability to bring it all together in a useful way. Sometimes, there's well-meaning (but ultimately unsatisfying) data standardization and consolidation efforts led by IT instead of the business.
These folks aren't really doing big data analytics, they're doing a pile of largely uncoordinated "small data" analytics. Taken together, it's "big", it's just not as effective as it could be.
The good news? These people are awash in valuable data. They "get" that there's untapped value there. And, if you look at it, they're spending boatloads of money around the topic, but they're just not getting the value from their investment.
Personally, I'm starting to believe that they just need a see the potential of what I call a more efficient producer/consumer relationship.
As an example, the Analytics Lab workshop from Greenplum has proven to be very effective in getting that "aha" moment going that changes business perspectives on how best to get to the next stage.
Group 3 -- The "Data Unengaged"
For me, the most frustrating group are those that appear to be in the middle of extremely valuable and compelling information streams -- they're just not really aware of the potential.
Valuable data is never captured, or discarded after capture, or kept for an unrelated reason, e.g. compliance. There's usually a full-time staff that laboriously gathers fragments of operational data across the organization, and builds spreadsheet after spreadsheet.
And, of course, when business leaders meet, there's rarely a single source of "truth", leading to incredible frustration, which somehow becomes IT's fault.
I worry for these people. Really, I do.
The world is shifting to an information-first model, and somehow they're firmly oriented to improving the legacy business vs. creating the foundations of the next one.
Speaking strictly as a technology vendor, this is not strictly a technology problem. I see it as a leadership issue. Although I have seen more than a few IT leadership types speak out loudly that there *is* a rationale for doing things differently.
What It All Boils Down To
I think the core difference between the "haves" and the "have nots" is the degree of information awareness. Not by IT, but by the business itself.
- What data sources do we have access to?
- What other data sources could we easily get to?
- What sorts of new business value -- from tactical to strategic -- could be gained?
- What sort of new skills do we need in the organization to do this?
- What sort of technology platform do we need to enable this?
This is not rocket science. This is not a lengthy and expensive consulting engagement, either. Too bad that it's probably not well represented in most MBA coursework :)
I think it's just realizing that having large amounts of information sloshing around isn't really a problem.
It's more of an opportunity.
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