Data is pouring into organisations of every size and type from every channel of the digital world. Data has become the lingua franca of business, revealing customer insights, buying habits, and new types of consumer. At the same time, opening internal windows into organisational performance - and functions such as Finance, HR, and Accounting - helps the organisation to be more efficient and profitable.
But that massive influx of data does not mean that every organisation knows how to capitalise on it, rather than be overwhelmed by its sheer volume, variety, and velocity. Extracting real value - the critical fourth ‘V' - is a strategic challenge as enterprises strive to become better guided by their data.
A Computing survey of over 150 data and IT leaders from a cross-section of professional markets, including banking, finance, manufacturing, logistics, retail, and government, found that nearly half (over 46 percent) describe their data strategies as either "moderately successful" (31 percent), "somewhat successful" (10 percent), "not at all successful" (three percent), or they lack any data strategy at all (three percent).
By contrast, just 20 percent describe the outcomes of their data strategies as "highly successful", with the rest (one-third of respondents) placing themselves in the "largely successful" bracket - good, but could do better.
The cultural challenge
So why are nearly half of organisations struggling, and what are the big challenges to turning enterprise information into a dynamic business asset - as opposed to a stockpile of inert or redundant data?
From the survey, the most frequently noted obstruction is cultural resistance within the organisation, cited by 45 percent of IT leaders. Structure comes a close second, with bad visibility of data between line of business units (observed by 40 percent of respondents) and poor integration between LOB applications (37 percent), revealing that legacy on-premise applications and internal structure are inextricably linked.
These obstructions are followed by a lack of the requisite skills among employees to extract business value from data, a problem mentioned by over 36 percent of respondents.
Taken together, the results may suggest that innate caution and conservatism - together with a lack of structural manoeuvrability in many organisations - could be mitigating against technology disruption and digital transformation.
Either way, the lack of appropriate skills may be feeding into poor concerted action. For example, non-technical employees may lack the ability to use data analysis tools to their full potential and so need the input of data scientists or analysts.
Thinly stretched staff
However, the survey also reveals that one-third of organisations believe that data analysis/science teams are "too busy to do their bit" - a challenge that should be met by strong leadership, good management, and new investment in staff and training.
The combined effect of the big three obstacles - organisational culture, structure, and lack of skills - is reflected in answers to another question in the IT leaders survey.
Computing asked how easy it is for respondents to engage in data-guided decision-making in their organisations, on a scale from one (very hard) to five (very easy). While 44 percent selected either option four or five, the largest single group of respondents (36 percent) chose option three - another middling result. Nineteen percent - one-fifth of all respondents - opted for option one or two, revealing that their organisations find data-guided decision-making much more challenging than their peers.
One reason for this is the persistence of data silos in many organisations - the knock-on effect of disparate legacy on-premises systems (and the processes that support them) growing in an ad hoc fashion over many years.
Looking specifically at internal functions, such as Human Resources, Payroll, Finance, and Accounting - systems that should be integrated to create a 360-degree view of performance - only one-quarter of IT leaders report that these are fully integrated, so that HRMS users can access Finance and Payroll data in real time, for example.
Although one-third of users report moderate integration and data sharing, 42 percent admit to either limited integration or complete separation.
The need for leadership
The answers to this question suggest that, in a majority of organisations, people, applications and data are at least partially ‘siloed', so while decision-making has become more data-guided in many enterprises, it still falls short of the strategic goal of extracting maximum value from data.
One way to tackle these entrenched problems is to appoint a Chief Data Officer or equivalent to be responsible for data collection, storage, and governance, as well as deriving value and actionable insights from that data.
But one person alone cannot make this strategy a success, even when driving it from the top of the organisation. He or she needs a network of executive peers to support their vision and sell its objectives across the business.
Encouraging operational staff to come on a journey to data-guided decision-making is the crux point between strategic decisions and real organisational action.