When CMOs and CIOs play nicely together, magic happens, and the chances of achieving a sustainable competitive advantage from data analytics are dramatically improved.
However, when the lingering indoctrinated divide between these two previously discrete disciplines isn’t addressed then it’s probably time to start updating your CV…
It's not exactly breaking news that data analytics is a rapidly exploding field within Australian businesses, with different organisations and industries across the country at different stages of maturity. ADMA estimate that around 30% of Australian businesses are currently at some point on the big data continuum between data discovery and data commercialisation.
The potential value of all of the data available to enterprises and SME’s cannot be underestimated; fact is, in our Information Age the competitive advantage will rest with those businesses who are best able to harness their data in order to make real-time decisions that protect their customer base and grow market share. With this in mind, why is it then that only 30% of businesses are taking action with their data?
In November last year, Hitachi Data Systems Corporation (HDS) released a survey of Australian and New Zealand businesses which revealed that, despite our eagerness to implement big data projects, we still had a couple of genuine hurdles to overcome. The first issue is an organisations big data strategic skills, the second issue is its quality of internal communication.
According to Neville Vincent, senior vice president and general manager, HDS APAC who commissioned the “The Hype and the Hope: The Road to Big Data Adoption in Asia-Pacific” report, the key challenge for organisations hoping to generate returns from big data was acquiring the right skill sets and managing communication better across the enterprise and between departments.
One of the most common examples of poor cross-departmental communication on big data projects is seen when you consider the recently emerged organisational imperative of achieving a Single Customer View. Typically, the goal of the SCV is simple – by better understanding its customer base an organisation is better able to achieve a bottom line return from said customer base. The problem, however, is that achieving a SCV is usually the goal of a siloed department like sales or marketing.
What many companies find out the hard way is that an SCV project is equally as much an IT ‘capabilities’ project as it is an ‘ROI driven’ marketing one. The challenge then in delivering an SCV project that delivers organisational returns by taking into account the needs of the CIO and the CMO is that both parties need to put aside the enduring power struggle over who owns the budget.
Accenture estimate that by 2017 CMOs are projected to spend more money on information technology and analytics than CIOs, as such, the days where CMO’s and CIO’s quibbled over budget ownership and varying departmental priorities cannot continue. The recent explosion in the adoption of Information Technology to drive sustainable competitive advantage is forcing Chief Marketing Officers and Chief Information Officers to work more closely than ever before.
Bridging the gap between these previously discrete disciplines has never been more important because in this Big Data era we live in it will be he (or she) who leverages their data better who will possess the greater competitive advantage. How do we get there? Through the CMO and CIO developing a common language and understanding of each other’s roles and priorities, and then working together to achieve the much larger organisational goal.
It’s this issue of fostering genuine cross-departmental collaboration that is the driving premise behind Australia’s first CXO Data Summit to be held in Sydney, September 18. The invitation-only Summit aims to bring together an exclusively C Suite audience for a day of Big Data thought leadership from some of the industries finest, providing an intimate environment for senior executives to converge, debate and discuss the major strategic issues they face in Big Data.
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