Today, data is an expensive resource. Collecting, maintaining and leveraging data for various business operations is putting an unprecedented amount of pressure on existing IT infrastructure. Bad data management has proved costlier than earlier estimated to such an extent that it could result in a “crippled” organization. According to a recent report, global businesses lose $2 million annually due to various data management challenges. As global organizations are scrambling to raise their data management proficiency, most of them are losing value and relevance due to a lack of technology for automation and workforce optimization. Poor data management could end up costing them dearly in lost productivity and missed opportunities.

The latest study, conducted by Vanson Bourne for Veritas, surveyed 1,500 IT decision makers and data managers across 15 countries. It reveals that data management challenges are having a severe impact on employee efficiency, productivity and the profitability of businesses around the world.

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Employees are First-Level Customers of Any Enterprise Data Management Framework

As the application of data across various business domains grows exponentially, data managers and analysts are expected to identify and plug gaps between various components of Data Management Platforms, including digital assets and analytics.

• On average, employees lose two hours a day searching for data, resulting in a 16 percent drop in workforce efficiency.
• Organizations that invest in effective day-to-day management of their data have reported cost savings and better employee productivity as a result.
• 70% of the respondents say they have reduced costs, while over two-thirds (69 percent) say their employees are now empowered to be more productive.

Lack of Investment in Data Management Could Hamper Revenue Goals

Beyond productivity challenges, the wider consequences of poor data management can cripple organizations. Almost all (97 percent) of the global organizations surveyed believe they have missed valuable opportunities as a result of ineffective data management. In fact, over a third (35 percent) admit to losing out on new revenue opportunities while two in five (39 percent) say their data challenges have caused an increase in operating costs.

Alarmingly, respondents estimate that their organization loses over $2 million a year due to challenges faced with managing their data.

Companies that fail to address their data management issues also risk significant longer-term damage to their business. Those surveyed say their challenges with managing data mean their ability to make strategic decisions is hindered (38 percent), they’re less agile (35 percent) and unable to compete successfully in the market (29 percent). Over a quarter (27 percent) are more vulnerable to data security threats, and 25 percent have experienced customer dissatisfaction.

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Managing Data with Data

As IT managers and top-level decision makers look to build a strategic approach to manage data, they need to look at areas of innovation at scale. The report identified athree-tier strategy to bring the focus back on effective data management. These are:

• Data Classification
• Policy Enablement, including for security, storage, and maintenance
• Automation using AI and Machine Learning

Traditional Customer Support Will Disappear

According to Ryan Lester, Director of Customer Engagement Technologies at LogMeIn, in the next five years, customer service — as we know it — will disappear.

Ryan said, “Customers aren’t all going to magically know how our latest gadget works or be able to break-fix when something goes awry with a phone or tablet. So, the need for our IT experts will certainly remain, but how they are deployed may look very different. As AI-powered tools are continuing to mature, we are seeing them deployed more and more within customer service and support environments. They’ve been incredibly successful in helping customers fix simple, repetitive issues. And as that continues to improve, it means less waiting time for customers and more challenging work for the service teams.”

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He added, “The result will be that while the work L1 technicians do today may be handled by AI, but what it will do is open a tremendous opportunity for those agents to elevate their role within the organization and do more impactful and strategic work. We’ve been talking about the theory of shift left quite a bit this year and we are going to see that come into practice in 2019.”

To ensure enterprises manage data well within their existing frameworks, it is important to switch the strategy to accommodate the adoption of right technology, right talent and the right expectations supported by strong senior management.