Although the term “big data” is rampant throughout corporate corridors, executives and business leaders have their own ideas – and sometimes misconceptions – as to what’s meant by big data and what it entails for the enterprise.
For instance, mention big data to some execs and they’ll hit you with a number of false impressions such as big data is new, it’s expensive, it’s complicated, and it’s best suited for use by highly-trained data analysts.
Such misunderstandings can make it tough for CIOs and other big data evangelists to set the right expectations among senior business leaders as to what big data is and how it can be utilized to optimize business performance.
Here are five ways that CIOs can clarify the big data discussion so it will resonate with key stakeholders.
1. Provide a clear definition of big data. Simply put, big data is the volume of structured data (e.g., CRM databases) and unstructured data (e.g., Excel spreadsheets, social media threads) that’s available to a company to gather, analyze, and act on.
Big data is not not just the volume of data that’s available to a company. It’s also the velocity, variety, and veracity of data (commonly known as the 4 “Vs” of big data, as Jacqueline Simard notes.
CIOs who are able to articulate what this means to business leaders will have a much greater chance of eliminating any myths that might exist and bring senior management and other layers of the organization onto the same page.
2. Enlighten business leaders on the costs/ROI of big data. Just as big data analytics can provide decision makers with insights on a range of topics – evaluating employee productivity, gauging customer engagement and their correlations to business performance (changes in revenue, customer value, etc.) – there are multiple ways to measure the returns on big data investments.
“Big data allows brands to interface with customers more strategically and measure the results of these interactions with great precision,” according to USTelecom.
Still, it’s important for senior management and other stakeholders who are investing in big data initiatives to be aware of the costs – including the fact that the cost to acquire, store, manage, and analyze big data isn’t a one-time cost.
3. Offer a clear example of how big data can be applied. Providing senior executives with clear, tangible examples of big data in use is a great way to tell a story.
For its part, McDonald’s has shifted from evaluating average metrics at local stores to using trend analytics to gain a much deeper understanding of what’s happening at individual stores and take appropriate actions.
The company combines data sets from across different functional areas and visualizes it to better understand the cause and effect as well as the differences between individual outlets.
4. Subtract the “big” to demonstrate that it doesn’t have to be complicated. Some business leaders are awed by the term “big data” as they read or hear stories about the massive volumes of data available and they wonder how their IT teams can possibly manage and make sense of it all.
This presents an opportunity for IT leaders and analytics evangelists to underscore the leading-edge analytics tools that are available for different classes of users – from neophytes to data junkies – to use to dig into data, visualize data, see it from different angles, and unearth as-yet undetected customer, business, and operational trends.
5. Show me the money. “The good news about all the hubbub around big data is that it creates an opportunity to talk about, and get funding for, data-related initiatives,” says Patrick Gray in a recent blog post for TechRepublic.
For CIOs, working with senior management to understand and identify their organizations’ top priorities is a great way to determine where to invest in big data analytics initiatives and to measure their impacts on expected outcomes.
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