GE CEO Jeff Immelt once said “If you went to bed last night as an industrial company, you’re going to wake up today as a software and analytics company.” Easy enough, right? Not exactly.
In the age of the Internet of Things (IoT), the challenge is that companies need to become a software and analytics company, while also remaining an industrial company. It’s pretty tricky. Software companies and industrial companies have many differences especially in the way they are organized.
Let’s look at the top 6 challenges facing companies looking to strike that balance between old and new.
Industrial giants rose to greatness in the Rust Belt, and Detroit has long been recognized as the historic heart of the automotive industry. In contrast, the boom of software companies today has put Silicon Valley, Boston, and the Research Triangle on the map. And there’s little to no overlap with the historic industrial hot spots. In fact, software companies are spread all over the world because they don’t have to concentrate employees in the same place.
It’s hard to find the right talent, and there’s a lot of competition. The software industry is clamoring for talent, and now the industrial industry is clamoring for that same talent. With demand greater than supply, it makes other factors like location and culture even more important to attracting and retaining top talent.
3. Culture / age
The new, younger workforce comes with its own expectations of flexible work hours and plenty of perks like free food and ping pong tables. The award-winning culture of many technology companies is appealing, especially to younger employees, while larger, older industrial companies are often seen as stodgy and rigid.
4. Clock speed
The development process has evolved from the waterfall model’s linear and sequential way. Its largest disadvantage is that it doesn’t allow for changes later in the lifecycle. Now that changes to software and digital content can happen in days or even hours, many favor the Agile methodology, which works in short sprints and is highly iterative. It makes it easier to add features that incorporate the latest developments, but it is also an entirely new way of working.
5. Investment profile
A typical industrial company might only spend 5 percent of revenue on engineering, while a software company may spend 15-30 percent (if not almost all in the case of startups). This flexibility comes from investment in operating expenses (mostly people), rather than the capital expenses industrial companies must front.
6. Business model
The “as-a-service” business model helps companies increase value by leveraging technologies such as cloud, automation, analytics, and mobile. Though largely still untapped, one successful example is Rolls-Royce’s power-by-the-hour program for aircraft engine use and service. Another is Trane Inc., a world leader in providing heating and air conditioning services, which is selling building comfort rather than individual products like compressors, boilers, or fans.
While industrial companies face many obstacles, there are key changes that can and should be made to transform a classic organization structure and ready it for the future.
Fix the Disconnect
IT and R&D are traditionally separate departments. IT has a supporting function, but now they need to be in the starting lineup also providing networking expertise to R&D. With these two departments working together as one, everyone is a winner.
Create a unified data organization
PTC President and CEO Jim Heppelmann uses the following comparison: “Data is the new oil. Analytics is the new refinery that converts a crude product into a valuable byproduct. But whose job is it to run that refinery?” Not everyone can take all the data coming in and do their own analytics against it. There needs to be a more unified approach, which is why the new position of Chief Data Officer is becoming more common. In fact, 61 percent of CIOs want to hire a CDO within the next 12 months, according to a 2016 Information Management trends report.
Data also inspires a more proactive approach to the customer relationship. Customers used to be the sensor of the product, but now the product is actually a sensor of the customer. It can tell the manufacturer how happy a customer is. Analyzing the incoming data can identify potential customer service issues before the customer even calls.
The recent creation of Development and Operations (DevOps) has given rise to a new breed of companies embracing a new organizational structure. Thanks to the modern software development lifecycle, we’re moving away from having one shot at manufacturing the product. Changes can be made even after a product ships. But how do you go about introducing those changes that are out in the field being used? Enter DevOps, which bridges the gap between IT, R&D, and service.
Learn from others
The changing nature of products is putting pressure on the organizational structure of companies, which means that you’re not alone. Several models exist already on how to best adapt.
When you merge a physical and digital company together, not everything will fit naturally and in the obvious places. The challenges, complexities, and changes may not be resolved overnight, but companies committed and dedicated to success and change will find the balance and tap into the all the potential of the Internet of Things.
- Cross business unit steering committee: a cross-functional committee who champion opportunities, share expertise, and facilitate collaboration
- Center of excellence: a separate corporate unit without P&L responsibility but is a cost center that business units can tap
- Standalone business unit: a separate new unit with P&L responsibility in that supports the IoT strategy and brings new offerings to market
To learn more about the topics discussed in this article, check out “IoT and Implications for Organizational Structure,” a MIT Sloan Management Review webinar with PTC President and CEO Jim Heppelmann.