Frequently, when we hear about how companies are using analytics, we hear about the rainmakers who found a “gold nugget” about customer behavior buried deep in the data and how they’ve used that insight to transform their sales and marketing.
It’s not surprising. In some ways, applying advanced analytics capabilities in sales and marketing initiatives can be considered the “low hanging fruit.” Sales and marketing are measured on lead and revenue generation, and they can often map a direct course from the data to new revenue.
While sales and marketing remain the top beneficiary of analytics, our recent interviews with more than 1,000 business executives suggest that R&D, HR and supply chain represent the next frontiers for analytics exploration.
If you build it, will they come?
Savvy enterprises are recognizing that the “build it and they will come” mentality to product development is no longer viable in today’s fast-moving, consumer-driven market. Continual analysis of how customers are using products, what they think about the products, and what problems they have using the products, can help build greater understanding of customers’ needs and, ultimately, better products.
It’s likely why our study participants indicated that R&D would see a greater upside from the use of analytics over the next two years—a 42 percent increase in those saying this function would benefit most. Whether they’re analyzing usage data captured electronically by the products themselves, social data, like blogs and reviews, or audio content from call center recordings, companies are seeking ways to improve sales success at the earliest stages of product development.
For example, one telco we spoke with said advanced analytics has helped the company more precisely identify where to invest resources. They’re replacing what they referred to as a “crude” approach—building out the infrastructure across an entire city — with a much more “surgical” approach—using in-house and third party data to “find the most profitable neighborhoods to upgrade.”
The data enables them to answer such questions as which streets are more likely to want HDTV or where their competitors are weak. It’s a huge change from how the company operated just two years ago.
Another interesting use of advanced analytics in R&D that I ran across is satellite TV provider Sky Italia. Sky Italia’s “product” is delivered in the form of program schedules. But when it comes to TV schedules, they’ve found one schedule doesn’t fit all.
Using social media data, the company has been able to customize program schedules and on-demand content based on what customers are talking about. Since the initiative’s May 2013 launch, 4.5 million customers are said to have benefited from personalized treatment.
The CTO describes the transformation this way: “We used to know little about our subscribers except maybe where they lived and what TV package they had. Now we know what they love to watch.”
How will you unlock the potential of your #1 asset?
I recently read about the Waratahs Rugby team in Australia, and the organization’s work to predict player injuries by using data. The team’s athletic development manager refers to the players as the team’s “#1 asset,” and says “if we don’t manage our assets, then our business—winning football games—will suffer.”
The Waratahs management sums up what leading companies have long recognized—that employees are an organization’s greatest asset. This certainly echoes what our research indicated: HR will be another fast-growing area for analytics over the next two years—with a 31 percent increase in organizations expecting this area of their business to benefit most from analytics.
There are myriad ways that advanced analytics can help companies use their labor resources more effectively, and the IBM workforce analytics study highlights the many external and internal factors—from labor market trends and regulatory issues to pressing workforce challenges—that are driving the increased need for workforce analytics.
Today, customer satisfaction and call center data can help managers uncover skill gaps and training needs. Internal HR data combined with external data sources, such as industry job listings, can help HR identify when high-value employees might be at risk of leaving. One restaurant chain we interviewed is correlating customer loyalty data with sales data so they can “schedule the employees who sell the most for its busiest shifts.” They reported a roughly 2 percent increase in revenue because of this.
Back to the Waratahs Rugby team. Their work may offer a few ideas to industries where on-the-job injuries occur frequently. Using data from several sources, including accelerometers players wear that measure intensity levels, collisions and fatigue, staff can anticipate and help prevent injuries and build specific regimens that better train individual players. As the story says, “injuries were once an unavoidable reality of sports; now data-driven teams can prevent them for a competitive advantage.”
Is your supply chain agile and adaptable?
While our research only showed a six percent increase in companies expecting supply chain management to benefit most from analytics over the next two years, I think that it’s an important area to highlight. Data and analytics can help address many of organization’s fundamental supply chain challenges.
Blizzard Ski, for example, offers a compelling case for companies looking to better predict demand. They’re using data to forecast ski trends, weather patterns, and other market shifts so they can “quickly respond to changing demands in specific ski towns.”
According to the company’s CIO, “With real-time data, we can produce what the market needs, when it needs them. A few years ago that wasn’t possible.”
Combatting fraud is also a huge issue for many manufacturers, and the Consorzio del Formaggio Parmigiano Reggiano—a consortium of Italian cheese makers—shows how advanced analytics can help companies spot fraudulent products in the marketplace faster.
The organization says that “if it doesn’t have our milk, it’s not our cheese,” so they’re analyzing market and product data of member dairies to “track the milk and confirm the legitimacy of every round of parmesan.”
Forward-thinking enterprises like these are recognizing that there’s huge opportunity in using analytics to solve fundamental challenges within every functional area of their organizations.
What business challenges can analytics help you solve today? What will be your next frontier?
You can learn more about GenD companies in “Inside the mind of Generation D.”