The Role of IT in Big Data & Analytics: Myths, Realities & Practicalities
By: Peter D. Moore President Wild Oak Enterprises, LLC
There has long been a challenging relationship between IT and its key internal line of business partners and other key stakeholders. Everywhere you look today someone is trying to undermine the CIO and the role and value of corporate IT:
- Shadow IT, technology purchases that bypass corporate IT, are growing at double digit levels.
- Long standing adversarial relationships between IT and its internal business partners and users have furthered a “legacy mindset” that believes “IT takes too long, costs too much and never gives me what I really want.”
- Lastly, many companies still see Corporate IT as only a cost center/support function rather than a direct contributor to driving new revenues and profits.
A recent study by IDC and the SAS Institute had shed new light on this issue through the lens of Big Data and Analytics and will be the focal point of a May 15th webcast http://go.sas.com/qgw6fr. The study states right up front that “success with Big Data requires enterprise-wide data coordination and cannot be performed by individual departments or shadow information technology.” It also highlights the continuing disconnect between IT and lines of business with regards to analytics. “While IT sees itself contributing to and guiding analytics strategy, LOB is more likely to see it as a roadblock.”
The core thesis of the study is supported by four key findings that debunk commonly-held analytics myths. What follows is a three part review of these findings with my POV added on the Practical side of the equation.
Myth #1:
IT controls all things data
Reality #1:
Analytics is finding a home, but not in IT
Practicality #1:
As a practical matter, companies must come to the realization that in the new era of digital interactions their customers and employees are now asserting their desire and role to control direct access to and utilization off data and data analytics. As such, both IT and the LOB’s need to see the value and benefit of letting go of a silo based control model and jointly support a cross enterprise access and utilization model.
At the core of the new digital business model is a company’s ability to leverage and deploy big data and data analytics as a driver of new revenues and profits. To do that successfully requires the full participation and collaboration of all the key stakeholders in the company working against mutually agreed upon business outcomes and deliverables. No one functional area or business unit can hope to have anywhere near the desired impact that this collaborative approach can deliver.
One of the major drivers of the new era of digital interactions is the demand by customers for “friction free” engagements. What consumers are looking for from companies is to be able to engage with them as easily as they engage with their family and friends using a variety of applications and tools:
Web has made searching for information friction free
Mobile has made access friction free
Cloud has made computing friction free
Big Data & Analytics are not yet friction free
Here are some examples of companies who are working to deliver friction free customer engagements:
Charles Schwab – Remote Deposit Capture
FedEx – Re-Route Your Package Delivery Location in Transit
Hyatt Hotels – Eliminate Lobby Check-In
Myth #2:
Technology poses the biggest challenge
Reality #2:
The greatest stumbling blocks are organizational mindset and culture
Practicality #2:
I agree completely with the IDC finding. The legacy mindset about IT that “it takes too long, it costs too much and it never gives me what I really want” is a major roadblock within most organizations. To overcome these stumbling blocks, IT and its business partners to a find a way to work together to align future technology investment priorities with critical business outcomes.
This process strongly relies on the cross enterprise distribution of data, information, knowledge and expertise in order to achieve that kind of outcome. It also must recognize and account for the fact that the customer now wants, in fact demands to be, more in control of how they engage with a company instead of the other way around.
Myth #3:
Everyone understands the value of analytics
Reality #3:
Businesses have trouble articulating the value of analytics
Practicality #3:
I think IDC’s finding is very true. If you look at the whole area of big data and data analytics and you talk to someone who is not a data scientist most of them do not have a clear understanding of what you are talking about. So we need to create a common vocabulary and set of terms and definitions that allows IT and LOB executives to have constructive dialogues about how best to leverage big data and data analytics for the competitive benefit of the entire enterprise. I think we have to make it easier for people who aren’t “experts” to be able to consume, discuss and utilize data in a way that’s very different than they have in the past.
Myth #4:
You can’t have analytics without IT
Reality #4:
IT is part of the problem, not the solution
Practicality #4:
As a practical matter, you can’t have analytics without IT because they are the keepers of the critical data that is stored by the company either on premise or in the cloud. That said, IT also has to let go of their old silo mentality where they wanted to control everything. They wanted to make it. They wanted to own it. They wanted to control access to and utilization of it. That is no longer possible.
As I said above, in order for companies to provide “friction-free” customer experiences, they need to enable them to have direct access to and utilization of data and information when they want it, where they want it and how they want it.
Going forward, I think IT has the opportunity and I would even say the responsibility to act as a catalyst to breakdown the old silo mentalities within their organizations and foster the utilization of a new collaborative, cross enterprise model to engage with their LOB executives and other key stakeholders.
