3 things I learned about Data at MIT
Is all data created equal? Who owns the data? Who gets to decide what it’s value is? Who is in charge here?!
Last week I found myself in the most unlikely place. I was back in the classroom, notebook spread open, vigorously scribing notes and hanging on to every word of Professor Sandy Pentland, one of the most cited authors in computer science and Forbes’ Top 7 most powerful data scientists!
The overfilled lecture hall at the prestigious Massachusetts Institute of Technology served as the home base for MIT’s 10th Annual Information Quality Symposium hosted by the MIT Information Quality Program at SSRC, the MIT Sloan School of Management, and the International Conference on Information Quality. Over 300 attendees, 19 sponsors, and acclaimed guest speakers filled the room.
The goal was to combine the brightest minds, CDO’s, CIO’s, enterprise technology leaders, and cross-industry specialists to deliberate data strategy, governance, and answer burning questions about modern data decision-making.
Companies have been deriving business value from data for decades, but now, according to Gartner, more than 30% of organizations will be directly or indirectly monetizing their information assets.
That’s right, monetizing data, as in data = value = dollars!
As a sponsor and representative of SAP’s Data Enterprise Platform Group, I got to join the conversation on data best practices, leveraging Big Data, managing culture in a rapid change environments, and getting ahead of the curve.
Turns out, all the senior data and innovation executives have the similar challenges when it comes to managing information quality in their respective fields.
Here is what we learned:
- Not all Data is created Equal: There’s personal data, demographic data, geographic data, behavioral data, transactional data, transportation data, military data, and medical data. There’s historical data and real-time data. There’s structured data and unstructured data. It often seems as if we are surrounded by growing mountains data. Also, there’s the same exact data points that vary based on “point-in-time” versus “point-over-time” which impacts the quality and “usefulness” of data. So,why care?
Well according to the MIT group of Chief Data Officers, “The failure to segment, audit, categorize, and clean data can be harmful- and very very very expensive for your organization”.
One insurance industry CDO said, “less critical data far outnumbers higher value data and spending the same amount of money protecting all kinds of data, regardless of its value has high financial implications”.
- Who is in charge? The Business: The Business MUST control the Data strategy, not IT. According to Sandhill Consulting, VP of Architecture Strategy, Donald Soulsby, “success means establishing a data strategy by first considering business goals, not technology solutions. Data is then the
“lingua franca” of any given organization.”- it’s the common language connecting the business.
The business is responsible for establishing critical data elements. IT will just provide the tools, stewardship, and management of the common agreed language across the organization.
Let’s consider the Oncology of Wine (a personal passion). If the businesses’ goal is to drive consumers to say a nice Pinot Noir, the critical data elements set by the business have to match the same result.
One path can be:
Red> Light > Pinot Noir
Another path can be:
French > Burgundy Region > Pinot Noir
IT will incorporate all relevant metadata, yet the Business must define all possible critical data elements to achieve the desired impact.
- Data is a corporate asset: No-brainer?! Well data still does not show up on the balance sheet but, it’s critical to your bottom-line.
More than 80% of business executives surveyed by Gartner believe data is on the balance sheet, tucked under other intangible assets.”It, I’m sorry to say, is not,” said Laney (Gartner, Doug Laney, VP & Distinguished Analyst).
Organizations are using data to increase revenues, reduce costs, improve customer service and loyalty, and improve employee satisfaction. Organizations like the Department of Transportation, Department of Defense, US Bureau of Economic Analysis and GE all invest in data—including the people, processes and technology required to manage data—proportionally to any other corporate asset, including cash, securities, people, equipment, facilities and intellectual property (McKinsey & Company).
Not a new field but, the majority of organization still struggle to properly assign economic significance of information.
Why is it important to quantify information value? (D. Laney, Gartner)
- You can use information as currency
- Productize information
- Collateralize Loans
- Assessing risk that contacts, judgments, & insurers deny information is property
- Claiming M&A valuation premiums
- Gauging what to spend on information security and tools
- Projecting and confirming ROI on IM initiatives
Biggest lesson? You can’t manage what you don’t measure