Four elements of a sound data strategy
Four elements of a sound data strategy
Four elements of a sound data strategy
With the accelerated shift to digital, many organizations are focused on how to effectively harness data to drive better decision-making, more efficient workflows, and improved business outcomes. However, the reality is that companies are finding it a challenge to create an enterprise-wide data strategy that achieves these ends.
In a 2021 executive study on the progress of big data and artificial intelligence (AI) initiatives in Fortune 1000 companies1, only 30% of companies reported having a well-articulated data strategy. However, organizations are at a pivotal point when it comes to developing a data strategy that is aligned to their business objectives. In a recent study of 200 C-suite executives that EXL sponsored with Forbes Insights, data-confident CXOs ranked themselves as “very successful” across a range of digital initiatives more often than their peers2.
In a recent panel session at #TechFT Live, I was asked how business should think about big data vs lean data, and what businesses should prioritize when it comes to data collection and analysis. As I think about how we advise customers on their data strategy, there are four elements that come to mind:
1. Scalability: The amount of data that organizations receive has multiplied, often by three or four times, in the last few years. Unstructured data is growing at 55-65% each year3. Whatever data strategy an organization develops must be flexible and scalable; it must account for the fact that we don’t know today what data may be needed in the near future, as business requirements, regulations, and technology are all subject to rapid change.
2. Linkages: Every organization faces similar challenges when it comes to data that sits across disparate and legacy systems. In many cases, business owners are concerned that sharing their data will lead to additional complexity, and don’t clearly understand the value they will get in return. The Chief Data Officer role was actually created to combat this problem and break down data silos across departments and acquired companies. The sooner businesses can get to the point of using data for the full profit of the enterprise through a defined data strategy, the better.
3. Cost: Cloud investments are expected to grow 12% in 20214. And there’s no question that cloud technology is cost effective when it comes to data storage. However, companies need to strike the right balance when it comes to storage costs vs computing costs as they think about the amount of data they need to collect and process to create insights across their business.
4. Return-on-investment (ROI): Organizations should think of their data as an asset and use it to their advantage. I encourage customers to look at their data with a business lens and think about the true value of their data and what it is worth; is it producing the magnitude of return one would expect and can that be scaled?
When it comes to digital transformation, the genie isn’t going back into the lamp. To achieve success with data-led initiatives, organizations must embrace this change and foster an organization-wide cultural shift in how they think about their data, and their customer’s data. When organizations center their data strategy around these four elements, they can quickly turn data into a sustainable competitive advantage.
View our recent white paper, Data as the driver of speed to value, to see how EXL’s data strategy and data engineering capabilities can power breakthrough results.
Citations
1. Why Is It So Hard to Become a Data-Driven Company? (hbr.org)
2. EXL-IG-Forbes-CXO-Insights.pdf (exlservice.com)
4. Cloud Infrastructure Spending Decreased in Second Quarter of 2021 But Is On Track for Growth in the Full Year, According to IDC
By
Vivek Jetley,
President and Head of Analytics, EXL