The Chief Data Officer’s Data Management Requirements
From the recent, MITCDOIQ event, I have already shared the “7 reasons why the CDO is here to stay”. Today, I want to dig in on the key functions of the CDO. To do this, I will use the football analogy suggested by Tom Davenport during the event. With this analogy, Tom claimed that CDOs need to play defense and offense. And just like football team, a good offense is often built upon a good defense.
Tom suggested the following things be in CDO’s defensive and offensive toolkit:
Defense: data security, data privacy, data integrity, data quality, regulatory compliance, and data governance
Offense: analytics, insights, digital transformation, data products, and customer relationships
Why putting the toolkit together matters?
Organizations have more data available to them today than at any other period. From interaction data to traditional data sets, organizations now have the data at their fingertips to optimize key business processes and as well as create new business models. The latter can increase revenue while creating new sources of competitive advantage.
According to Jeanne Ross, those wanting to continue to win in their markets need to use their data to implement one of two digital strategies–customer experience or value-added digital business services. Look at General Electric’s move from physical assets to asset performance management. In an independent commissioned study conducted by Forrester Consulting on behalf of Informatica, they have found that a significant driver of the nascent CDO role is in fact the threat of digital disruption. Digital disruptors are emerging which uniquely have data and predictive analytics at their core, and they are using this to create competitive advantage and barriers to entry against incumbent market participants.
A good defense starts with data governance and quality
It should come as no surprise that Chief Data Officers need to start by fixing their company’s stewardship of data and put in data quality controls so that their organization’s data is trustworthy and usable for business decision making. In today’s world, data management practices are needed that deliver the real-time insights to drive predictive and prescriptive analytics models. One financial CDO put the challenges this way, “If you don’t understand what data is critical, and don’t actively monitor it, and don’t have quality checks, and have no standards, you don’t really know how your business is performing”.
At the same time, organizations tell us that they are facing intense regulatory pressure from contractual requirements as well as new government mandates like U.S. Patriot Act, the U.S. Affordable Care Act, FISMA, HIPAA, PCI, SOX, and Basel II, which require stricter enforcement of data security and compliance procedures.
CDOs clearly have a significant job ahead of them on defense. Passive approaches to automating antiquated and legacy processes are simply not enough. Chief Data Officers need to take a pragmatic approach to data management that leverages a universal understanding of metadata to extract greater business value from analytics, while protecting the organization from security and compliance failures.
A great offense is built upon a great defense
CDOs that are struggling to improve the data hygiene of their organizations, cannot build a world class analytics organizations. Validating this is the fact that most data scientists actually consider themselves to be more data janitors than data scientist. Most complain about spending too much time manually trying to find and, then, reconcile data that is fragmented, duplicated, inconsistent, inaccurate, and incomplete across their organizations. Traditional solutions to these challenges have required expensive, manual, and time-consuming processes or the integration of fragmented point solutions. Instead of quickly acting on newly acquired data, data analysts can endure weeks of waiting to get useful data. Without the proper policies, procedures, people and technology in place, incumbent organizations struggled to produce data that can be trusted and thereby, risk falling behind their competition.
Is a comprehensive solution possible?
An intelligent and systematic approach is needed that plays data defense to data offense. This solution should extract more business value from more data without incurring additional business risk. This solution should enable your organization to find relevant data and understand the relationships that matter for more accurate and targeted analytics including predictive analytics. It should also provide core capabilities around data integration, data quality, data governance, and data security capabilities and be delivered on premise and in the cloud. It should next allow for collaborative data preparation and enable analysts to quickly curate and share data, while collaborative and rule-based data governance enables agile standardization and enforcement of data taxonomies.
Once the above defensive tasks are accomplished, it needs to enable offense by allowing data scientists as well data explorers to discover data relationships and then build advanced analytics models directly in open source tools like Spark. With this, CDOs can allow their organizations to truly go from defense and offense and assemble the winning team to deal with digital disruptors.
It is possible to streamline the data supply chain. By creating repeatable data processing, it is possible to deliver trusted business-critical information assets anywhere, so the right decision makers have right data at the right time. With this in hand it is possible for data scientists to focus on discovery of data relationships and then building data models. If you want to learn more about CDOs, please join us to hear guest speaker Gene Leganza, Vice President, Research Director, Forrester discuss independent research that validates the CDO role and mission.