Addressing Data Dyslexia

Everybody thinks they know what data is, but it seems that few really understand and appreciate the value of data to a business, writes Jeremy Wilcox.

SOMEONE WHO WANTS to correct ‘data dyslexia’ is DataGenic’s Managing Director, Richard Quigley who terms data, “The lifeblood of a company and its most valuable strategic asset,” yet concedes, “most companies don’t have the same opinion.”

Quigley’s mission is to change this view and promote the value of data as a strategic tool, explaining, “I want to align my thoughts on data to help companies realise the value of this powerful and valuable asset.” In the business world certain functions and disciplines are seen as ‘sexy’, like trading, portfolio and risk management, having an almost magnetic allure that attracts people to develop a career in these disciplines. There is a perceived glamorous value that makes them appear to be a significant contributor to the overall success of a business.

Quigley believes that most people erroneously perceive the function and discipline of data management as a ‘non-sexy’, – tier 3 level role within the organisation. “They find the concept of accepting equal parity between an asset such as a power plant and data too abstract, and are unable to visualise its business value and strategic importance. However, the irony, indeed paradox, is that without data, these physical assets would have limited value.”

But let’s not be too gloomy about this apparent data dyslexia. Investment banks and the larger finance players, explains Quigley, provide the right example on which to build. The focus of banks on data management and their appreciation of the value of data are well known and documented – although their implementation in some respects fell short of completeness. For example, last year a well know insurance company struggled to understand what assets made up their balance sheet. However, even with this apparent ‘implementation shortfall’ finance organisations are still streets ahead of the energy industry on data. The smart ones have employed data tsars and chief data officers for years with these personnel having board representation.

There is an interesting innovator-laggard relationship between the investment banks and the energy sector. Rewind almost two decades and it was the innovative banks that introduced over-the-counter derivatives and the concept of front-to-back office risk management systems into the embryonic energy trading sector, and consequently encouraged energy companies to view energy both as a physical and financial asset. Yet this transition to a more financially-orientated, less risk adverse approach to trading is still somewhat of a novel business model to an energy sector that some would argue has still to recover much of the lost confidence from the demise of Enron in December 2001.

However, Quigley is an optimist and puts the current trading mentality down to a difficult learning curve for many traders, with a number of large energy companies/utilities still to come out of their post-government mentality, adding: “Over the past five years these companies have been bringing in quantitative analysts to help with the complexity of the market and to realise more value from trading and operations.” So data progress is being made within the utility sector – it’s just that it has some way to go.

As with the adoption of more creative derivative contracts the energy industry should also, believes Quigley, follow the lead of the investment banks on data management. He explains that while the banks have employed seamless integrated data and risk systems the energy sector is still using disparate, inefficient and ‘not fit for purpose’ data management practices. At the same time, they deploy the Rolls Royce of risk systems. It really does contradict the very essence of what risk management is trying to achieve, Quigley observes, when the data being used in the system has a complete lack of quality control, transparency of computation and traceability of source.

With the intellectual prowess of some talented individuals in these companies, it is still hard to believe that irrational and risky practices are being condoned day after day in some of the largest companies in the marketplace. As Quigley notes, “Treating data as an afterthought to your gilt-edged downstream system is a recipe for disaster.”

There are numerous ‘war stories’ in the marketplace where poor data has contributed to financial losses, explains Quigley, including lack of verification of grid settlement charges due to lack of cohesiveness between consumption and contract data, high imbalance charges from using poor quality forecast data, re-invoicing of contract settlement due to inaccurate data, and losing deals to a competitor or losing money from structured deals due to missquoting from inaccurate or incomplete data.

Clearly the energy sector needs a wake-up call on data, particularly if it is to survive the post recession green economic transition era. Individual corporate losses will provide their own wake-up alarm, but companies shouldn’t have to make losses before realising that some investment in a data system could not only mitigate them but also increase competitiveness and profitability.

Whist investment in data expertise and technology from a leading specialist like DataGenic will help, Quigley argues that investment is also needed at the top of the company in the appointment of a chief data officer, which he says is fundamental to the strategic data management function.

Wikipedia defines the role of chief data officer in very lucid terms: “Besides the revenue opportunities, acquisition strategy, and customer data policies, the chief data officer is charged with explaining to executives, employees, and customers the strategic value of data and its important role as a business asset and revenue driver. This is in great contrast to the older view of data systems as back-end IT systems.”

Unfortunately, the energy sector has got it back to front. It has bought in data doers, not leaders. Exhibiting board-level data leadership and ownership is a bold move, but one that pays massive dividends, even in the short term.

The challenge facing the energy sector as we approach a new decade is to better understand and value data, with Quigley explaining: “Energy companies have to believe in the value of data and adopt an asset-based investment and maintenance model, not simply pay lip service to it being an asset. They must invest in data and make it work for their company. Only then will they realise and benefit from data’s asset value.”

Complying with European regulatory directives, such as MiFID or the proposed Third Energy Package, may only encourage a verbatim adoption to ‘pass’ the compliance test other than actually encouraging a more dynamic utilisation of this data. Ultimately, there is a need to invest in data and data management practices, as the market will always adopt the Darwinian theorem: only the strongest and the smartest will survive.

If wake-up calls fail, and regulation remains too passive on data, then the only medium left to push the data management vision are the data management system vendors, of which DataGenic is an industry leader and data management visionary.

DataGenic can bring value to the market, explains Quigley, by providing a coherent, objective and complete view of data management that a company may not identify. “As a company, we want to bring best practice, we want to innovate and develop new ways to realise data value; robust frameworks – such as workflow applications, allowing full data transparency and traceability throughout the data lifecycle, datatype agnostic data management systems – to ensure holistic and centralized data views forming the platform to allow the creation of more value from data with the application of Artificial Intelligence, business rules and natural language processing.”

Quigley continues: “A realisation that Excel cannot run your business in today’s competitive and complex landscape will help to start the process of a strategic data management programme.” Simply put, Quigley’s mission is to challenge conventional wisdom that data is a cost and inputting into the asset, rather than data being the asset.

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