The industry buzz about “big data” has been growing for years. But many organizations are still wondering how to invest in data-driven processes, and whether the business impact from those investments will pay off over the long run.
Today researchers from Keystone Strategy shared results from one of the most in-depth studies yet that seeks to answer these nagging questions. Representing the first comprehensive research project that quantifies the difference between enterprise data leaders and the so-called “laggards” who are less mature in their use of data, the study and its associated white paper were published by Marco Iansiti, Karim Lakhani and Robert Bock, and sponsored by Microsoft.
The study outlines dozens of specific measurements, but the overall impact is clear: Companies who use data effectively follow a different trajectory for profits, with gross margins that are 18 percentage points higher and operating margins that are 4 percentage points higher. These differences translate into margins that are an average of $100 million higher, a consistent gap that holds across industry and company size. Data leaders profiled in the study also experience greater employee productivity, generating $507,000 in average revenue per employee versus $473,000 for those falling behind.
“We see that the best firms are deploying information technology and analytics more broadly and doing the most sophisticated job,” says Iansiti, a Harvard Business School professor who is also chairman and co-founder at Keystone. “It’s clear proof that these technologies really work in firms.”
The research team surveyed 344 large companies worldwide, focusing on upper midmarket and enterprise organizations with a median of 6,000 employees and $3.4 billion in revenue. Participants cut across geographies and industries ranging from retail to insurance to manufacturing. Keystone probed key areas such as technology investment and the organization’s approach to data, and investigated actual business performance in sales and marketing, engineering, operations, finance and other crucial business functions.
“What’s interesting about this research is that we actually reviewed specific business scenarios and processes,” Iansiti says. “This gave us a detailed, under-the-hood look at the status of data and analytics technologies inside each firm, along with very good measurements of operational and financial performance. We were able to identify a strong correlation between the two.”
The results show a startling difference in company performance — a large and potentially widening gap between leaders and laggards across nearly every metric. It’s indicative of a new economic divide with potential to mark a significant milestone in the evolution of business. Companies not embracing their own digital transformation could find themselves woefully behind the competition, and in some industries older business models could be phased out entirely.
“What we’re seeing today is a testament to the fact that waves of new technology have washed over the operating model enterprises use and changed what managers do today in a fundamental fashion,” Iansiti says.
Interestingly, the study demonstrates that the difference between companies leading or falling back is not determined by IT spend. Researchers found only a negligible difference in IT investment as a percentage of revenue between leaders and laggards — less than 1 percent.
Instead, results indicate that the divide has more to do with companies’ operational mindset with regard to data, and the sophistication with which they’ve mapped their data technologies both to operations as well as the overall market.
“The big difference is that they’re really using the technology hand in hand with managerial practice to drive good decisions,” Iansiti says.
Perhaps as surprising is what the researchers didn’t find. When it comes to success in data science, there was no appreciable correlation between older, more traditional companies and younger ones that grew up in the cloud era. Instead, researchers found examples of companies both old and new succeeding with data. Iansiti says that’s because success requires a real understanding of customers and the overall market, an area where more established firms could actually have a built-in advantage.
“Doing this well means integrating across the more traditional capabilities of really knowing your customer and knowing your business,” he says.
While the study sounds an alarm bell for companies that may be falling behind, the good news is that organizations do not need to single-handedly build the technology to get started. The software industry has been innovating in this field for years, and today companies can leverage the power of the cloud, advanced data platforms and services at a lower cost, and with a much faster time to value.
Microsoft’s Barb Edson, who as general manager of data analytics and Internet of Things (IoT) for the Cloud and Enterprise product marketing team has worked with dozens of companies to help infuse analytics and intelligence into their operations, says the technology today is mature enough that companies can start creating value right away. The crucial ingredient is not a lengthy implementation, but simply a commitment to making it happen.
“To have a data culture, you’ve got to get your hands dirty,” Edson says. “We’ve seen a lot of great success stories, and those companies share the same characteristics: They are willing to do trials and proof of concepts. They’re willing to invest in partnerships with experts and try new technologies. It’s the willingness to lean in, even in starting small and looking at where the true impact lies, that leads to success.”
Another critical element is knowing where to invest to achieve an impact. To do that, companies need to have the right team in place. The study shows that top performers have established strong cross-functional teams, including strategists who understand the business and technologists who can work with large data sets.
But according to Edson, it’s not necessary to assemble a team of data scientists in-house before you begin. Tapping outside resources and communities can help propel innovation for companies in the early stages.
“We often work closely with systems integrators and other partners to engage and provide customers with the right skill sets,” Edson says. “Whether customers build it in-house or we help them bring the right talent to bear, an end-to-end solution is very achievable.”
For companies just setting out on their data analysis journey, Edson has another piece of advice: Be prepared for changes to your operating model and business strategy. Data insights may compel you to reshape the way your company approaches engaging with customers. It may transform products and services or empower employees to contribute in new ways. Often these changes enable a company to realize new opportunities and even become a disruptor in their market.
“Instead of just driving efficiencies, you’re actually having a business-model epiphany,” Edson says. “We’ve seen companies transform their entire industry from insights gleaned from data and analytics. In the end they have a whole new way of thinking about their business that they didn’t dream of before.”
Take the Data and Analytics Maturity Model Self-Assessment
Is your company a leader or a laggard? Microsoft is offering a Data and Analytics Maturity Model Self-Assessment. This is a great first step for organizations to learn where they stand, and uncover individualized approaches to take their data capabilities to the next level. Visit www.microsoft.com/datamaturity to take the assessment, review detailed results of the study and explore additional resources.
Microsoft News Center Staff