(SPONSORED) Industrial leaders face a crossroads of opportunity. Digital transformation, the Industrial Internet of Things (IIoT), the emergence of Industrial AI, generational churns in the workforce that are leading to a loss of decades-old domain expertise, and data management strategies that have hinged around mass data accumulation for years. These competing pressures are all collectively pushing our sector into a cloud-ready, AI-powered digital future. That’s precipitated the rise of new digital executives and IT leaders in our industry, too: chief technology officers, chief information officers, and especially chief digital officers (CDOs), who are tasked with taking advantage of these new opportunities to drive their organizations into a successful industrial digital transformation.
But accomplishing that requires being clear-eyed about some of the critical hurdles that stand between CDOs and the digital transformation they’re working toward. Here are three key areas that CDOs and other industrial digital executives need to tackle ensure their organization undergoes a successful and value-adding digital transformation.
1. Bridge the gap between legacy systems and new technologies
Digital transformation hinges on combining efficiency with innovation, but businesses often forget the latter. The CDO’s role in driving industrial digital transformation in no small part must involve updating all of a plant or facility’s legacy systems to ensure the company is both talking the talk and walking the walk in embodying the digitalized spirit.
CDOs have to first identify which new technologies -- like IIoT sensors, the intelligent edge, next-generation data historians, and fit-for-purpose Industrial AI applications -- are capable of delivering better outcomes, and then lead the charge on implementing these technologies across their plants. This isn’t a case of delegating new product installs to the IT team. The change must be led from the top to ensure this gap between legacy and new technologies is bridged on a structural level. Without that guidance from the CDO, the results won’t deliver the ROI expected, undermining both the value of the digital transformation itself and the CDO’s ability to get buy-in for future digitalization projects.
2. Foster collaboration across silos
Whether we’re talking about functional silos, data silos, or technology silos, silos are a reality in our industry. They’re also a major impediment to digital transformation. Facilitating that transformation means CDOs need to be able to identify the overlapping business needs between different siloed segments of the organization, and foster cross-collaboration where needed.
Silos impede the ROI that industrial organizations make into innovative new technologies, like Industrial AI. For example, a new independent survey found that 88% of industrial organizations across North America and Europe utilize either in-house or contractor AI and machine learning experts -- yet the majority of these experts, data scientists, and analysts either work completely in silos or have minimal collaboration between them. How can organizations be expected to tap into the value of Industrial AI if most of the people using it aren’t communicating with each other? Consequently, the same survey found that, on average, key IT and operations decision makers in these organizations do not have full visibility into 66% of their organization’s industrial data.
Successful digital transformation, including optimizing the ROI on new technologies like Industrial AI, depends on CDOs being able to bring together different corners of the business that own disparate data sets, technologies, and workflows.
3. Rethink data: integration, monetization, and security
If data integration and monetization represent the CDO’s offensive line, data security is where they need to play defense. The price of recent data breaches across various industries has been extremely high – recent IBM research pegged the cross-industry average at $4.24 million, a 17-year high water mark. In the industrial sector, loss of data or production downtime caused by such a breach can be a mission-critical disaster. In the aforementioned Industrial AI survey, data security topped the list of most commonly cited challenges for data management and quality (41%), followed by data being stored in disparate locations (39%), a lack of skills to derive actionable insights from data (37%), and a lack of skills to manage data effectively (35%).
CDOs and other industrial digital leaders have to rethink the role of data across their organization. Data security follows from stronger data management and quality practices. Meeting the challenges of this moment requires a shift in thinking, from the mass data collection mindset of years past toward more strategic data collection -- with an emphasis on data value over volume. More thoughtful and strategic data collection practices and workflows result in higher-quality and specific industrial datasets and greater visibility, making it easier to integrate data, leverage it for refined productization, and place it in more secure formatting stages.
This is by no means an exhaustive list of what CDOs and industrial digital leaders face. But by bridging the gap between legacy and modern technologies, breaking down team, data, and technology silos, and shifting gears from mass data collection to more strategic data management, CDOs can put their organizations on the right footing for executing, and reaping real value from, a successful industrial digital transformation.
Bill Scudder is AspenTech’s Senior Vice President and General Manager of AIoT Solutions. AspenTech’s AIoT Hub provides the foundation for Industrial AI, including flexible data mobility and integration from on prem to the cloud, and empowers customers to get actionable insights faster than ever with next-generation industrial AI solutions. Bill previously served as Senior Vice President and Chief Information Officer and remains responsible for the company’s IT organization. He has more than 25 years of IT leadership experience, developing and implementing mission-critical, global technologies and building the operations and IT organizations to support them.