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With the global landscape changing at a frenetic pace, an organization’s ability to be agile and make productive use of data is now central to its long-term success.
Companies able to harness data’s full value will likely leapfrog those struggling with technology and organizational change. Experts suggest up to 6% of global output is at risk over the next decade, a result of the digital divide between those able to capitalize on data and those still struggling to figure out its role and what’s at stake.
“It’s very clear that in this environment, which is changing at unprecedented and unexpected levels, that agility and the productive use of data has become more important than ever,” said Svenja Falk, managing director at Accenture Research, during a panel on the “New Digital Divide” at the 2022 MIT Platform Strategy Summit. “If you want to tackle that, you must start with things that you can influence.”
Experts laid out four directives for improving companies’ ability to reap the rewards of data and a platform-based ecosystem:
1. Understand the true power of data.
Many companies are stuck evaluating data through the traditional lenses of quality, cost, safety, and productivity goals. However, advanced industrial technologies like Programmable Logic Controllers and Supervisory Control and Data Acquisition systems have changed data types and how frequently data is collected, opening up new possibilities for value. These systems interface with industrial sensors to collect a wider range of data, often in near-real-time, paving the way for data-driven insights that can fuel new services in areas like predictive maintenance and ensuring plant floor performance.
Supheakmungkol Sarin, head of data and AI ecosystems at the World Economic Forum, identified four ways companies can tap into data’s value: to establish new revenue streams; to underpin new ecosystem-enabled business models; to deliver richer experiences for customers, users, suppliers, shareholders, and partners; and to drive real-time insights and make better decisions.
To do any of these, data must be made accessible and useful for the broader enterprise, a practice which is still a struggle for most.
“It’s about democratization — getting data out to the broader organization, understanding what data means, what data we need, what data we don’t know we need yet, and experimentation,” said Peggy Gulick, director of digital transformation operations at manufacturing company Kohler Co. “It’s all about how you get to that next level of using data to truly be innovative and drive advancement.”
2. Scale up projects for impact.
Experimenting with data is critical to the process, but the key is turning early wins into something that can have broad impact and promote enterprise digital transformation. Starting small with a targeted proof of concept remains core to the strategy. Yet it’s still possible to scale pilots fairly quickly with the right governance and guardrails in place and by making sure people have the right tools and mindset to put data to work to solve problems.
“You want to prioritize the digital value and push it down so that people have the ability to change the way they work,” Gulick said.
To ensure that level of democratization, Kohler employs a hub and spoke model, leveraging a smart factory user interface and big data lake that enables individual plants — Gulick has oversight of 63 plants in different countries — to test innovative use cases on their own.
“We don’t want 12 people sitting in a corporate office saying, `Hey, we’ll do this next,’” she said. “We want to have those employees coming in on a daily basis with problems to be able to reach out with the right processes and tools” to drive data’s value.
Once successful, the initiatives will scale by way of Centers of Excellence, a multidisciplinary group that advocates best practices, and through word of mouth. The company wanted to give plants autonomy to spend their own funds and drive improvements, Gulick said.
“It’s not fast, but it’s the right approach from a culture and transformation perspective,” Gulick said.
At Schneider Electric, the key to scaling data initiatives is standardization — both technology and business processes, according to chief digital officer Peter Weckesser. To do so, the firm has established “power couples.” This matches a business process owner and a technologist, both tasked with evolving business processes and technical architecture and collaborating on a data roadmap.
“If you want to drive scalability, this has to be a business transformation project, and that’s organized very differently from a classic IT project,” Weckesser said. “It’s not like getting a specification and the IT organization acts as an order taker and implements.”
Schneider Electric is also emphasizing standardization of not just technical architecture, but also data platform architecture, master data management, and data models.
3. Orient key stakeholders.
Having senior leadership commit to data initiatives is a must, but many don’t have adequate understanding about the role of data, let alone pivotal technologies like artificial intelligence and machine learning. They also don’t always fully grasp relevant issues associated with newer concepts like ecosystems and AI ethical frameworks.
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Leadership tends to get stuck in old patterns, such as viewing data as a potential revenue source or liability. This is limiting, Sarin said.
“When we talk about data-driven value, it’s all about trust,” Sarin said. “Instead of viewing data as a source of revenue or risk, we should think about empowering stakeholders and our ecosystem as a whole. Having a trusted data environment that enables that ecosystem should be the way going forward.”
Strategic alignment is also essential, from a top-down perspective as well as from the bottom up. It should be supported by an active change management program.
“That alignment becomes the North Star — a vision that can be communicated to investors and customers,” said Schneider Electric’s Weckesser. “It’s a lot of hard work to drive that through the whole organization.”
4. Formulate a platform vision.
Companies can garner real value by moving beyond data silos to data platform ecosystems that include customers, partners, even competitors.
Industrial company Siemens used this strategy to their advantage. During a period when its competitors promoted their own communications platforms, Siemens made its intellectual property available through PROFINET, a separate organization and ecosystem, according to Helmuth Ludwig, a professor at Southern Methodist University and the company’s former CIO. The ecosystem approach created value and netted Siemens about 1% market share gain each year, he said.
“If you think purely in the normal traditional pipeline value creation, you’re probably missing a key element,” Ludwig said. “If you think ecosystem value creation and trying to get your fair share, then you are on the right track.”
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