Business data users

Chief data officers: the new 'Big Data czars'?

The chief data officer is an emerging position tasked with overseeing projects that aim to derive value from enterprise data sets: some observers think that CDOs could assume a defining role in shaping corporate success for the next 10 years.

As data is increasingly perceived as a dynamic asset, more thought will be given to how best to manage it – not only in terms of storage, availability, quality and analytics, but also the architecture that allows for data being accessible and ‘malleable’. 

Bigger data management covers IT, business strategy, statistical analysis and more. Accordingly, the job title of chief data officer (CDO) is becoming more prevalent in executive hierarchies, although some estimates suggest that there are now only 150 CDOs in organisations around the world.

However, market-watcher Gartner has recently predicted that by January 2015, 25 per cent of large global organisations will have appointed CDOs. Gartner also reckons that some 65 per cent of current CDOs work in the US, while 20 per cent are UK-based; there are, however, CDOs in over 12 countries now, the analyst reports. In addition, over 25 per cent of CDOs are women – that’s almost twice as high as the proportion of chief information officers (CIOs). This is most common in heavily regulated industries, media and government, Gartner found.

According to a recent report in the Financial Times, the speed with which organsiations are appointing CDOs “will not only define the shape of business, but also the next generation of men and women who will lead them”.

Standard specifications of a typical CDO’s roles and responsibilities may differ from enterprise to enterprise. According to one standard definition, CDOs are responsible for enterprise-wide governance and use of information as an asset, via data processing, analysis, data mining, information trading and other means. They won’t necessarily report to an established CIO. Stuart Coleman, commercial director at The Open Data Institute (the business facilitation body founded by Sir Tim Berners-Lee and Professor Sir Nigel Shadbolt), agrees that the CDO “is essentially responsible for determining how data can be used across an organisation and the operational environment to drive better business outcomes.”

In a significant number of corporate entities a range of data has been (and is being) collected and stored, but has not really yet been fully assessed and interrogated for strategic gain. More companies starting to use data analytics tools across their business operations means that the CDO will play a pretty vital role in ensuring that data can make a meaningful contribution to informed business strategy. The standard appointment of a CDO in any organisation that values its ‘data estate’ would appear a necessity.

“Historically, data came within the remit of the IT department, and was seen as something to be stored – what has changed is that data is now an active asset that can have a lot of value extracted from it... It is therefore a business issue,” says Laurie Miles, head of analytics at business analytics software and services supplier SAS. “For some companies like Google, for example, the business is very data-centric. They treat this very seriously, and for them the CDO is a natural and important role. Other companies are further behind the curve on this.”

Appreciating the value of data

A sector that seems to be more appreciative of the value of data is banking and finance: it was shaken by lack of data visibility and transparency during the 2008 crisis. The retail sector too has recognised that it is not just the transactional data, but all the information around that which can inform future campaigns and distribution channels.

The telecommunications industry has also long-identified the value in its data – here it is not just the static data that is attractive but more the data on behaviour, social networks and suchlike that is ripe for harvesting.

Customer billing data, for instance, not only provides insight into usage patterns that can help forward planning, but also provides evidence of trends that could inspire new revenue-generating services and products. More recently the UK National Health Service (NHS) and central government are taking strides – sometimes controversially – to improve the quality of their centrally-held data, and to harness it to inform future strategy and make better informed and supported predictions.

“No matter what the industry, the trend is for there to be wide recognition of the benefit of data and that it is an asset,” acknowledges Chris Nott, CTO big data & analytics, IBM UK & Ireland. “The importance of deriving analytical insight from data has never been greater.” In practice this means that data needs to be able to look at the past, the present and then, on the basis of those, be able to predict the future. An early example of this, says Professor Jim Austin, CEO at data analytics company Cybula, was looking at data sets from aircraft taking off and using that to inform a maintenance programme for aero engine manufacturer Rolls-Royce.

‘Cleansing’ and preparing data to allow for a single view allows for it to be analysed not just for a single purpose, but in any number of areas. According to Nott, by applying analytics in one area – to identify fraud, say – there is an overall business benefit which then translates through to others such as marketing, profitability, inventory, etc, also being able to use the same data sets.

“The CDO making the right data in the right place at the right time gives an organisation the opportunity to innovate, and to harness data for better decision making and strategic policy,” Nott says. “It also gives better overall visibility and harmonisation – and standardisation.”

Indeed, creating that usable data set in the first place all comes down to how data is governed over the whole organisation. At Barclays bank, for example, firm-wide governance of data is something that is being looked with a view to simplification and gaining both efficiencies as well as a better overall quality of data.

In the NHS, meanwhile, information governance, which involves ensuring that the necessary safeguards are in place across the organisation for protecting and sharing information appropriately, is higher-up on the priority list. There is also a focus on information standards. The first two, thus, inform strategic intelligence and transparency – which, in turn, improve internal accountability. Accountability and regulation go hand-in-hand with good data governance and transparency.

The finance industry, one of the most heavily-regulated industries, was in fact one of the first to get behind the concept of a CDO because it needed to clean up its data provenance. “Banking is under intense scrutiny and pressure to change for the better,” says Barclays Bank CDO Dr Usama Fayyad, who was said to be the first person appointed to the role of CDO in his previous role at Yahoo. “One of the benefits of centralising data is that it can become easier to comply with regulatory changes. For example, if a business within Barclays is storing the same data in three or four places – and we move it into one central database.”

The data traction attraction

There are inherent advantages to having someone look after both the way in which critical enterprise data is prepared and stored, as well as the way it is then used for future decision making and strategy. IBM’s Nott describes the CDO as a critical lynchpin. “It’s become apparent that someone senior with an overview was missing,” he believes, “and putting into place the right expertise and mechanism to bring all that data together and make it work is now key.”

In practical terms this means that the CDO should serve as an executive interface between the various business branches – departments, directorates, project groups – and touch points that data has. It means working with the IT department to create appropriate systems architecture and the right environment to start working on the data analytics.

This aspect of the process will be scheduled in conjunction with a ‘data scientist’  or even what could be called an ‘enterprise statistician’, who would not necessarily be formally attached to the traditional IT function.

The Open Data Institute’s Coleman says that key to the skillset of the enterprise-wide CDO is being able to manage key relationships with all aspects of the enterprise from legal to marketing to compliance. “Marrying domain knowledge of your industry with a broad range of data experience and skills is critical to be able to know what questions you can – and should – ask of your data to make a difference to your business,” he explains.

CDOs are “most commonly from an IT background, but in the future the CDO probably more likely to come from a business background”, agrees Miles at SAS.  “They need to be able to identify a business problem, and then try to work out what data can do to solve it.”

He also thinks that Master of Business Administration (MBA) degrees should have a quantative analyst element incorporated into them – this would do much to help weave the data and the business knowledge together, he claims. Indeed, the challenge of having a CDO at anything other than enterprise-wide level is that there is a lack of overall insight. In an age of centrally-held single ‘golden’ copies of data, having anything other than an enterprise-wide CDO can start to seem a bit nonsensical.

Fitting the CDO into business

Barclays’ Fayyad says: “I view the CDO job as a mix between business and technical responsibilities. An effective CDO, in my opinion, must drive some business strategies as well as own technical execution and delivery with an emphasis on excellence in data management and access: both by humans (insights) and machines (systems).”

The way in which the CDO works with other data-related professional specialisms also varies. The Big Data vogue is causing many businesses and other organsations to rethink their strategic attitude toward their data ‘estates’, and part of that exercise is to look at ways to apply different forms of value to that data. Another aspect is to examine ways in which data generated and ‘owned’ by one part of the business could possibly be exploited by a different part of the business. There is potential for value-added cross-fertilisation, but some of the protocols on which data management has for years been based will have to be rethought.

“Data is owned and used by the business overall, but managed by IT,” says Jane Griffin, executive advisor at Deloitte Analytics Canada. “Within IT, however, a data manager looks at how the architecture can best serve the data – can it be consolidated? Can a different application be used? What are the IT governance roles to be applied around the data?”

Bringing the data to the table is then the role of IT. Being able to gain insight from it is the role of the data scientist or statistician who commonly sits within a business unit. “Directed by the CDO, the data scientists look at the data itself, and make it meaningful by devising the methodology and the modelling around it,” says the Open Data Institute’s head of statistics Ulrich Atz. “The CDO sets the direction, and data scientists provide the insight. They can be from a social science statistical world, where they are looking to find cause and prove a trend, or they can be from an IT background, a computer scientist or software engineer – and thus have strength in the architecture.”

Indeed, although data scientists do not necessarily have to have a background in IT, they are apt to be highly technical people. A deep knowledge in computer science or systems engineering is pretty essential in the background of an effective data scientist. And although statistics is a technical field, data scientists who are statisticians by training still have to have strong computational skills.

Interest in Big Data is no longer confined to corporate strategy documents. Soon stakeholders in the wider world – institutional shareholders, say – will start to expect a Big Data strategy to deliver value to the balance sheet. The number of CDOs looks set to increase as organisations realise the extent to which their data estates could be exploited for strategic advantage.

Future CDOs could come from IT, statistical, or computational backgrounds; but they also need to have the business skills to define how to make best use of data and drive data insight forward. Marrying technical and the business element together is rarely easily achieved, but is clearly required if organisations are going to successfully define and create the architecture required to derive insight.

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