This article originally appeared on HBR.org.
From targeted online advertising to more precise recommendation engines, consumer markets are bursting with innovation around machine learning and advanced analytics. While there’s less buzz around business-to-business markets, these innovations are changing the game in B2B as well, even in old-line industries selling what might be considered commodity products.
A growing number of B2B companies are using data and analytics to add services that bring new elements of value to customers, and in some cases new sources of revenue. These elements are fundamental attributes of a company’s offering in their most essential and discrete forms—things like product quality, flexibility, and associated expertise; they lift value propositions above commodity status and benefit customers in particular ways. (For a deep dive into the elements, see our related HBR article “The B2B Elements of Value”).
Consider recent moves by Australia-based Orica, which provides packaged explosives materials to mining companies worldwide. Orica’s explosives are being used in roughly 1,500 blasts per day, and until a few years ago, data on those blasts existed on bits of paper and in disparate electronic sources. Orica invested in digitizing all that data and combining it with data supplied by its customers, including the objectives of the blast, conditions of equipment at the site, the exact techniques and products used in the blast, and the outcome.
What do customers want? Bain's Elements of Value® represent the deeper aspirations behind the purchasing decisions of B2B and B2C customers. Our insights explore the ways companies can go beyond price to offer more value.
Orica used the data to build pre-blast modeling and post-blast measurement and analysis, packaged in a user-friendly online system called Blast IQ. The service provides benchmarks and insights to ensure sustainable, cost-effective improvements in blast performance. When a mining customer enters information about an upcoming blast such as geological data, drilling equipment data and the desired outcome, Blast IQ runs a set of sophisticated models to simulate blast outcomes. This enables engineers to fine-tune a “high-resolution blast” so that it produces more predictably sized rock and dirt for subsequent loading, hauling and grinding, which together account for most of a mine’s operational costs. Producing blasted rock of the proper size helps Orica deliver a crucial element of value: reduced cost.
Orica is now codifying the decision logic of the most experienced blasting managers through predictive modeling to serve up personalized recommendations on demand. And as customers use Blast IQ and contribute more of their own data, over time, the company will have a large enough dataset to train more powerful machine learning models.
Blast IQ thus delivers a whole new level of value to customers apart from the purely functional or economic elements—notably in the areas of enhanced productivity and a closer relationship with Orica. Through an “elements of value” perspective, we see that Blast IQ provides time savings, information and expertise. At an even higher level, Blast IQ helps a less experienced engineer move up the learning curve much faster than in the days when one learned strictly by trial and error. The service offers the possibility of enhancing an engineer’s marketability and growth and development.
In another old-line industry, agriculture, Monsanto has steadily enhanced its core commodity chemicals business with data and analytics-based services to expand the value elements delivered. One of its boldest moves was the 2013 acquisition of The Climate Corporation, which was founded by two former Google engineers who built on 30 years of free government weather data to help underwrite weather-related risks. The Climate Corporation chose to focus on agriculture given the size of the industry and the fact that adverse weather conditions are a leading cause of crop failure. They assembled a massive data set using soil sensors and field experiments. Monsanto folded the entity into its suite of farmer advisory services, and has continued to build a loyal customer base with additional mobile applications and advisory services.
Taking this strategy a step further, the company established Monsanto Growth Ventures (MGV), a venture fund based in San Francisco that looks for other inventive, environmentally sustainable ways to improve crop yield. In the past two years, The Climate Corporation acquired two of the companies in the MGV portfolio: HydroBio, a data-based, irrigation management platform that incorporates satellite imagery and crop models to improve the yield on water supply; and VitalFields, a reporting and tracking application that incorporates climate, disease and growth patterns to help farmers comply with local environmental regulations and better plan their season.
Starting from explosives and farming chemicals, these B2B companies have embedded their expertise in powerful software platforms to expand beyond the traditional products. They have enhanced the underlying data assets with search capabilities and algorithms that recognize patterns and make recommendations that can inform a complex array of decisions.
This kind of access to expertise and logic provides substantial additional value to B2B customers, whether through risk reduction, information or other value elements. In Monsanto’s case, this evolution also opens up opportunities to position the brand as a company that uses data and analytics to provide the elements of hope and social responsibility in farming.
Any product that requires some expertise to use is a candidate for analytics innovation. B2B companies that neglect this area could find themselves sinking into a commodity trap. Stores of wisdom and experience in their employees’ heads, hard drives and file cabinets cannot become valuable until they are packaged up and made accessible to customers. Machine learning takes all that experience, tests it in algorithms and delivers the best tailored answer more comprehensively than any human could.
Lori Sherer is a partner at Bain & Company in San Francisco and is co-leader of the firm’s Advanced Analytics practice. Jamie Cleghorn is a partner with Bain’s Customer Strategy & Marketing and Technology practices.