Data Silos Are the Greatest Stumbling Block to an Effective Use of Firms' Data
Data silos are cropping up across organizations. How can they be broken down to allow for effective data analysis? An industry executive gives his take.
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Greater access to data has given business leaders real, valuable insights into the inner workings of their organizations. Those who have been ahead of the curve in utilizing the right kinds of data for the right purposes have reaped the rewards of better customer engagement, improved decision-making, and a more productive business, whilst those who have lagged behind have found themselves faced with an uphill struggle to compete.
This, however, has only been the first part of the data story. As businesses have begun to recognize the positive impact data could have on how they run their business, they've taken a predictable next step: they're collecting more of it. And lots more.
Whilst the logic that more data means greater and more varied business insights is sound on paper, our research suggests that many businesses don't have a suitable strategy or the technological infrastructure needed to realize true business benefits from their growing data stores. We recently commissioned a survey of information technology decision-makers across US and UK businesses with 500 employees or more to examine enterprises' data ambitions, investment plans, and return-on-investment (ROI) expectations.
The challenge is clear: around three-quarters (74 percent) of our respondents believe their organization has more data than ever but is struggling to use it to help generate useful business insights. So what are the challenges and stumbling blocks that businesses are facing when dealing with their data, and what steps can they take to solve them?
Understanding Data Value
Firstly, it's necessary to find out what goals businesses have for their data. Nine in ten (90 percent) IT decision-makers agree that it's an increasingly high priority for their organization to be able to better utilize data, with 86 percent seeing this as a key means of gaining a competitive advantage.
Drilling down further, many are aiming to make more effective use of data to improve organization-wide operations. The most commonly cited goals were around improving business processes (64 percent), driving operational efficiencies and reducing costs (57 percent), as well as making business decisions more quickly (46 percent).
Alongside this, a number of data goals relate to improving the customer experience. Over half (54 percent) highlight improved customer service as a goal, and over a third (35 percent) say the same for providing more tailored and personalized customer experiences. This is hardly a great shock. For any business, understanding the needs of your customer base and being able to shepherd them through their purchasing journey more effectively is key to pushing revenue growth.
Data Investment and ROI
At the outset, I highlighted that the amount of data businesses collect and generate is due to grow significantly in the future, and that, even today, businesses are struggling to turn their data into actionable insights. However, this isn't from a lack of effort or financial support from within the business itself. This year, respondents' organizations have allocated on average $797,537 to operationalizing data. The expected average for 2019 jumps to $1,132,013, and in five years' time, it's expected to be $1,725,309.
This willingness to invest is easily explained when we asked about the financial benefits expected from proper data use. Respondents estimate that, on average, their organization would see annual revenue increase of $5,156,891. This equates to a staggering 547 percent return, or $4,359,354 gain, on the current average investment. However, to realize these lofty data ambitions, businesses will need to invest this budget appropriately, rather than risk throwing good money after bad.
The greatest stumbling block our respondents identified as hindering their attempts at better utilizing data is one that has existed for some time but seems to have worsened as data volumes have grown - data silos. Only 2 percent of our respondents considered their business to be completely effective at data sharing - for the rest, data silos are a real problem.
The causes for this are numerous, and span inconsistency of systems being used (42 percent), different data formats (38 percent), and a lack of coordinated data strategy (37 percent). On top of this, over a third highlight a lack of technology integration (36 percent) and/or legacy technology barriers (36 percent) as blocking attempts to effectively share data.
If businesses are to truly make the most of their increasingly large and complex data landscapes they'll need to ensure that they're investing in the right technologies. The issue of data silos is nothing new to businesses both large and small, but it's becoming far more pronounced as data stores grow and the move to becoming a more data-driven business is advocated by senior business leadership.
If organizations could invest in improved data integration technologies, as well as create a business-wide culture and strategy for better data sharing, it would go a long way towards improving the data-driven decisions being made across the business.
With nearly half of our respondents citing differences in how data is being collected, defined and managed across their company as a reason to mistrust it clearly, a unified, integrated approach to data is a reasonable first step to creating a more data-driven organization.
Published at DZone with permission of Gaurav Dhillon, DZone MVB. See the original article here.
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