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    The Office of Data Mandate

    At the Data Clairvoyance Group, we envision the Office of Data as a driver of business. Rather than viewing data management as a negative drain on resources, we believe that the Office of Data must be active in adding to the bottom line. Data, as an organization commodity, is the lifeblood of business, and it should be considered a source of innovation, operational improvement and revenue. Data optimization is a double ROI win: cost reduction and revenue increase.

    Our view is embedded in the Office of Data Mandate, the directive to ensure that data commodities are accurate, accessible, trustworthy, transparent, safe, and efficient for the purpose of creating economic value.

    But who in an organization will lead such an ambitious data initiative?

    The Office of Data Mandate requires a leader who can manage the people, process and technology necessary to handle data, but also the creativity, vision and quantitative skills to put the data to use in ways that are well beyond the scope of routine maintenance and incremental efficiency gains.

    The Office of Data Mandate requires the next generation of Chief Data Officer (CDO). Over the past decade, we have seen the evolution of this position through three distinct generations. Legislative mandates in highly regulated industries such as banking and finance effectively created the 1st generation CDO. The 2nd generation CDO brought Business Process expertise to the position. The 3rd generation CDO leverages Data Science to the position in order to exploit opportunities for data monetization. In the following section, we will describe this evolution in more depth.

    Evolution of the CDO

    “Data is about people. People create data. People move data. People consume data. People use data to make business decisions. Thus, a CDO should have the ability to work through people to improve the value of data.”

    – Bob Stanton, Chief Data Officer, Guggenheim Insurance Services

    Legislative mandates in highly regulated industries such as banking and finance effectively created the 1st generation CDO. The title of CDO propagated to the insurance industry and then to non-financial service industries. In the non-financial sectors, the CDO was still charged with ensuring that the numbers were in compliance with regulatory demands, but they also acquired more responsibility around choosing which data to collect, which to store and which to discard.

    In the rush to comply with the demands of regulation, the 1st generation CDO plowed money into technology. They wrote big checks to big companies that promised big dividends (think Master Data Management), but these dividends never materialized in terms of either enterprise efficiency or added business value. The investments only perpetuated the illusion that the liability of unwieldy data had been mitigated.

    The second wave of CDO arose out of the unfulfilled promise of these costly technological solutions. The new CDO still had to ensure regulatory compliance, but they also had to understand business processes in order to ensure their own career survival. They had to pivot toward the business in order to justify their large budgets to astute executives who were demanding ROI instead of a black hole of inscrutable technology costs.

    The 3rd generation CDO must speak the language of business while being able to communicate with and manage those who live in the IT world of servers, databases and SQL statements. Firms looked to the CDO to build a data-centric culture among all of those in the firm who touched, used or shared data. The CDO must understand the business processes that rely upon data, and they must be able to justify their budget in terms of the top line and bottom line. In fact, we believe that the biggest responsibility of the 3rd generation CDO is to have their own Profit and Loss accountability.

    Data as an Asset & Liability

    “Data becomes a liability when a company makes investment decisions without confirming the quality, definition, and understanding of a data field. When data fuels bad decisions, it costs the company money.”

    – Bob Stanton, Chief Data Officer, Guggenheim Insurance Services

    We know that some data can be an asset and should be treated as such. But data also presents liabilities in the form of operational risk, long-term operational costs (debts), potential unplanned capital outlays, and, if the data is bad, the effects of bad business decisions. While the cost of storing data is getting lower, data still requires significant investment in order to collect, store and adequately maintain. As the evening news reminds us, data security risks are endemic in organizations today. Stolen or lost data represents not just an internal loss, but is potentially ruinous to client/consumer trust and to the brand name.

    While some data is a known liability, some data is not apparently risky or useful – it just sits waiting to be used. This data may not be worth keeping because it is not useful in the current business model. It might be prudent to dispose of, but it just might be valuable at a later time, or to a different user. Taking a page out of Rembrandts in the Attic, a book that illustrates the hidden value of intellectual property patents, there is the nagging possibility, however small, that today’s trash could be tomorrow’s treasure. For example, historical data might be useful internally to tune current data models, or it might be externally sellable. Or it might just be junk.

    The cost of keeping data appears to be so cheap that the safest strategy is just to keep maintaining it. But there are real costs. Excess data can clog the system or divert attention from the good stuff. The CDO, in the context of the Office of Data, must have the knowledge and the judgement to decide what data is worth keeping, what data should be discarded, and what data can and should be exploited.

    Of course, the CDO must also have the machinery in place in the Office of Data with which to optimize and exploit the data that is worth keeping. This is where the investment in building a team and creating a data-centric culture pays the greatest dividends.

    Three States

    “There is an overemphasis on technology rather than a focus on organizational culture, people and processes.”

    – Gartner Research, The Business Case for the CDO

    Data resides in three states: The Physical, the Logical and the Conceptual. Physical data is what resides in the databases and in other electronic repositories. Logical data encompasses the schematics of the data eco-system design. Conceptual data resides in the minds of those who use the data. This is the most difficult data to access and is the most often overlooked, yet, the conceptual data is key to managing data on an enterprise level. Those who work with data ultimately determine if, and to what degree, data becomes an asset or a liability. The habitual interactions with data set the enterprise on a course of improvement, decline or stagnation.

    The most immediate goal of the CDO and the Office of Data is to effectively manage the data ecosystem consisting of data in the Conceptual, Physical and Logical states.  The most valuable long-term goal of the Office of Data is to develop data as an intangible asset class within the firm, which is to say that the CDO must protect and precisely manage the data liabilities of the firm and eliminate data that has no value and serves only to clutter the ecosystem. Data is both a liability and an opportunity. With the right culture, the data-centric firm will realize more of the opportunity and suffer less from liability.

    The Office of Data, led by the third generation CDO will solve business problems through delivering the right data no matter if the problem is related to growth, cost, new financial strategies or even customer experience. An exciting new application of data is to use artificial intelligence to improve the online customer experience. Through real-time use of data, the ‘smart’ app can predict, with reasonable accuracy, the needs and the preferences of the customer. The benefits of Amazon and Netflix recommendations are well known. Apple’s Siri and Amazon’s Alexa demonstrate how technology can make life easier by helping to accomplish mundane tasks a little bit faster. A smart CDO can work with an application development team to create a truly customized customer experience. For example, a smart app can minimize the customer’s data entry through inferring information from machine-learning driven analytics.

    Big Data or Big Clutter?

    To fulfill the Office of Data Mandate, a firm must have a robust team that is centered around data. Everyday, those inside the firm must understand that data is an asset that will improve or decay. The CDO in charge of the Office of Data must develop the right people, process and technology in order to attain data optimization.

    By now, many firms will say that their data is an asset and many executives want in on the big data Gold Rush, however, most firms have a hodge-podge approach. Some are storing evermore potentially valuable data and that they will never let go of. Some data scientists in the organization might have their own data silos that are out of sync with the rest of the organization. Some firms might be lured to dump their data into an innovative-sounding Hadoop cluster or MongoDB. They might be awed at the great expanse of their newly made Data Lake. But without a coherent plan, and statistically-driven insight into the storage, access and use of data, the Data Lake will become a gigantic Data Swamp filled with data unfit for use. The promise of big data becomes the burden of big clutter.

    Dumping unrefined data into a Data Lake is like trying to find the needle in the haystack by building a bigger haystack. Instead, what you really need is a powerful magnet. The well-run Office of Data directed by a 3rd Generation CDO will use discretion founded in advanced statistics and machine learning in order to cull data and create value – to find that needle. With big data comes big responsibility.

     

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