Mining Legacy Data Allows CIOs to Extract Business Insights
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Mining legacy data to extract business insights about the connected customer sounds like digital transformation heresy.
Think about it. Who else but your CIO has the best understanding of the trove of legacy data currently residing in data kingdoms?
By turning to back to basics and looking at already-existing data, the transformational CIO helps the enterprise mine for gold that’s been hiding in plain sight. By focusing on data mining for what is familiar, the CIO catalyzes the organization to become:
- Comfortable working with big data and predictive analytics;
- Conversant working with non-technical colleagues; and
- Focused on connecting analytics back to business value creation.
This was the message delivered by Nick Curcuru, Vice President, Big Data Practice, MasterCard, at the Strata Hadoop Big Data Conference in NYC last month.
Harness “what’s old” with “what’s new.”
When the CIO focuses on mining legacy data utilizing the right people asking the right questions from the right data sets, an organization discovers rich business insights about the now-very-connected customer.
Chances are when that legacy data originally was collected, those “right data tools” were not available. The “right people asking the right questions” were not yet employees.
Now your organization’s data mining stars are aligned.
It is one thing to collect and store data. However, the majority of stored data has a cost associated with it rather than business value created by it. Having loads of historical, unstructured data wreaks havoc on storage costs.
In the MasterCard big data business case, the teams asked the right question: Can we put legacy data into an open-source framework like Hadoop, apply analytics platforms and at the very least cut storage costs?
Then they realized they could do more than just store data more cost-effectively. They asked another right question: How can we take legacy data and turn it into actionable data, real-time, instead of reacting after the fact?
After all, comparing legacy data with current data extracts connected customer insights not only about what happened historically versus what is happening right now. Your organization is poised to anticipate and predict what will happen in the future.
When the right person, the CIO, works across the enterprise to “free the data” what type of business outcomes are produced?
Organizational innovation happens when the CIO and CTO spearhead projects to apply big data mining and analytics platforms to specific use cases. In a sense, these teams learn to collaborate through legacy data archeology. This process allows data scientists to learn to work more effectively with customer-facing business units. Just as the data is trained, so the cross-functional team is trained to ask the right questions about the data.
This strategy allows teams to ask even more relevant, specific and insightful questions. The MasterCard team moved away from focusing on data quality or data volume. Data scientists were tasked with doing more than analyzing data just to see what they could do with it. Instead, their focus became:
- Creating data sets to test the business applicability and value of the data set and the test;
- Learning to explain the value of test outcomes to non-data scientists; and
- Identifying when data patterns became valuable for a customer, their own company and to various lines of business.
To create digital transformation, allow the CIO to tie big data analytics back to the real world.
Curcuru recommended starting with specific use case drivers which are tied to known business metrics. This process allows for quicker data extraction, provides meaningful insights faster and also creates a protective sandbox in which the team can fail faster.
Create a pilot big data project which utilizes mining legacy data to extract already-known, historical business insights. Then evaluate how the breadth and depth of these historical insights are expanded by predictive analytics and real-time data analytics.
For example, instead of providing transactional services like credit cards, MasterCard realized they provided customers with information. They subsequently re-visioned their organization and evolved into an information company. Their output focused on interpreting, proactively as well as historically, the economic implications of customer purchase trends.
Transforming the enterprise into a digitally- and insightfully-driven one won’t happen overnight.
The biggest change, of course, is overcoming resistance to what is new. Curcuru stresses the value of continuous education as the CIO transforms the enterprise through nothing short of a change management project.
How is your own organization wrestling with digital transformation? Have you created pilot projects to allow cross-functional teams to identify the right questions and create the right data sets? Do you have a timeline set for moving forward towards enterprise-wide digital transformation?