Credit: Oshkosh
American automotive manufacturer Oshkosh Corp. has designed and built specialty trucks for more than a century. But for the past several years, the Wisconsin-based company has been ramping up its data capabilities to drive decision-making.
“We are focusing on developing predictive models for our businesses and functional areas,” says Anupam Khare, Oshkosh’s senior vice president and CIO. “In the last 18 months, we have developed roughly 35 analytic models.”
Those models have had millions of dollars’ worth of operating income impact.
Oshkosh, founded in 1917, makes specialty trucks, military vehicles, truck bodies, airport fire apparatus, and access equipment. It operates 147 manufacturing facilities in 22 countries and sells its equipment and vehicles in more than 150 countries.
When Khare joined the company in 2018 to oversee its digital transformation, Oshkosh’s data and analytics capabilities consisted of a small business intelligence (BI) group in JLG Industries, an Oshkosh company that specialises in designing, manufacturing, and marketing access equipment such as aerial work platforms and telehandlers.
Determined to help Oshkosh become more data-driven, Khare hired Marina Pashkevich-Zayed as vice president of advanced analytics and artificial intelligence from a consulting company in early 2019 with the goal of focusing on digital manufacturing, advanced analytics, and robotic process automation (RPA). Since hiring her, the company has built out a team of data scientists, data engineers, and data architects.
“We have been very lucky to hire great people in the Wisconsin area, which is not easy,” Khare says. “We have built the most diverse team. We also have two or three people whom we have trained internally, and they have also joined the data science team.”
Overhauling data operations
One of Khare’s first initiatives was to evaluate the company’s application portfolio and data to determine their business value.
That assessment found a host of inefficiencies. For example, many of the company’s applications weren’t integrated with its ERP system, forcing employees to manually transfer data from spreadsheets to other applications, or send the data to suppliers via email (as many as 200 per week). The team determined these manual processes were eating up about 8,000 people-hours per year.
As a result, Khare’s team focused on using RPA to connect key applications and the ERP system, automating the whole process. From there, Oshkosh has focused on building out predictive capabilities that help it forecast margins on orders and customers, decide where to bid for new business, and optimise its supply chain.
One of the company’s more recent projects, the Digitised Buying Experience, uses advanced analytic models integrated with a configuration tool to predict material and labour costs based on a truck’s unique configurations to give customers more accurate and timely quotes. The project has earned Oshkosh a CIO 100 Award in IT Excellence.
“Advanced analytics has now become a CEO goal, and I review the progress with the board every year,” Khare says.
In addition, once a quarter, the team does a joint review of analytics projects with the business units.
Prioritising value
To ensure analytics deliver impact, Khare’s team only builds out projects that have a passionate sponsor, and then prioritises projects based on expected benefit.
“A passionate sponsor means a businessperson who has a problem or pain points which analytics can help solve. Passion is the first element,” Khare says. “The second element is we quantify the benefits of the project on the company’s profit, which is operating income or sales growth.”
To help potential sponsors understand how data and analytics can help them, Khare’s team has developed a catalogue of roughly 100 use cases by functional areas that are intended as a conversation starter.
“Our team basically goes and does a workshop in multiple businesses and functional areas and educates them about the possibilities and that leads to a conversation,” Khare says. “We follow that process in new areas. What has happened in the areas where we have already delivered five models is the sixth idea coming out excels."
Khare also notes that the team seeks to align its data scientists with the company’s lines of business, giving the data scientists a lot more insight into each business and its needs. The result is that the data scientists have begun to speak in the language of the business and the businesspeople have begun to adopt the language of data, leading to more intuitive interactions and the generation of more ideas.
Khare believes that part of his team’s success is due to thinking like a startup within a big organisation.
“If we look at a startup, they put in some seed money, they take risk, and then they have to educate the venture capitalist, which in this case is the leadership,” Khare says. “We are continuously educating. This is an entrepreneurial process.”
Culturally, Khare says the team has a CARE culture, which stands for customer obsession, agility, results, and entrepreneurship. The IT and analytics teams emphasise those qualities via metrics and discussion. Khare notes there is an incentive award for team members who exhibit those behaviours.
“What we have learned is that focusing on real business opportunity and being a storyteller are the key to success,” Khare says. “Being a storyteller helps to expand and create momentum, and focusing on real business opportunities not only helps the business, but your IT-as-a-business capability.”
