(Sponsored) Industry leaders face a crossroads of opportunity. Digital transformation, the Industrial Internet of Things (IIoT), the rise of artificial intelligence, generational fluctuations in the workforce that have led to a loss of experience in the field decades ago, and data management strategies that have been revolving around the backlog of mass data for years. Together, these competing pressures are driving our industry towards a cloud-ready, AI-powered digital future. This has precipitated the emergence of new digital CEOs and IT leaders in our industry as well: CTOs, CIOs and especially Chief Digital Officers (CDOs), who are tasked with taking advantage of these new opportunities to drive their organizations to successful industrial digital transformation.
But achieving this requires being clear about some of the critical hurdles that stand between CDOs and the digital transformation they are working towards. Here are three key areas that industrial digital executives and other industrial digital executives need to address to ensure their organization undergoes a successful and value-added digital transformation.
1. Bridging the gap between old systems and new technologies
Digital transformation depends on combining efficiency with innovation, but companies often forget the latter. The CDO’s role in driving industrial digital transformation must in no small part include modernizing all legacy systems of the plant or facility to ensure the company is the talk and walking in embodiment of the digital spirit.
CDOs must first identify new technologies—such as IoT sensors, the smart edge, next-generation data historians, and fit-for-purpose industrial AI applications—that are capable of delivering better results, and then lead the implementation of these technologies across their factories. This is not a case of delegating new product installations to the IT team. He must drive change from the top to ensure that this gap between old and new technologies is bridged at a structural level. Without this guidance from the CDO, the results will not achieve the expected return on investment, undermining both the value of the digital transformation itself and the ability of the CDO to gain support for future digitization projects.
2. Strengthening cooperation across silos
Whether we are talking about functional silos, data silos or technology silos, silos are a reality in our industry. It is also a major barrier to digital transformation. Facilitating this transformation means that CDOs must be able to identify the business needs that overlap between the various isolated sectors of the organization, and promote mutual collaboration when needed.
Silos hinder the return on investment that industrial organizations make in innovative new technologies, such as artificial artificial intelligence. For example, a new independent survey finds that 88% of industrial organizations across North America and Europe use artificial intelligence and machine learning experts either in-house or on the contract — yet the majority of these experts, data scientists, and analysts either work entirely in silos or have Minimal cooperation between them. How can organizations be expected to benefit from the value of artificial intelligence if most of the people who use it are not communicating with each other? Thus, the same survey found that, on average, key IT and operations decision makers in these organizations do not have full visibility in 66% of their organization’s industry data.
Successful digital transformation, including improving ROI on new technologies such as artificial intelligence, depends on CDOs’ ability to bring together different angles of businesses that possess disparate data sets, technologies, and workflows.
3. Rethink Data: Integration, Monetization, and Security
If data integrity and monetization is a CDO’s line of attack, data security is where they need to play the defence. The price of recent data breaches across various industries has been very high – a recent IBM research pegged the industry average at $4.24 million, a 17-year high. In the industrial sector, data loss or production disruption caused by such a breach can be a mission critical disaster. In the AI survey mentioned above, data security topped the list of the most common challenges to data management and quality (41%), followed by data stored in disparate locations (39%), and a lack of skills to extract actionable insights from data. (37%), and a lack of skills to effectively manage data (35%).
CDOs and other industrial digital leaders need to rethink the role of data across their organizations. Data security follows stronger data management and quality practices. Meeting the challenges of this moment requires a shift in thinking, from the mindset of collective data collection in years past to more strategic data collection – focusing on the value of data over volume. More thoughtful and strategic data-collection practices and workflows lead to industry-specific, higher-quality datasets and greater visibility, making it easier to integrate data, leverage it to improve production, and put it into safer coordination stages.
This is by no means an exhaustive list of what CDOs and industrial digital leaders face. But by bridging the gap between old and new technologies, deconstructing team, data, and technology silos, and shifting gears from mass data collection to more strategic data management, CDOs can put their organizations in the right place to execute, reaping real value from an industrial digital transformation. successful.
Bill Scudder is AspenTechSenior Vice President and General Manager, AIoT Solutions. AspenTech’s AIoT Hub provides the foundation for AI, including flexible data mobility and integration from start to cloud, and enables customers to gain actionable insights faster than ever before with next-generation AI solutions. Bill previously served as Senior Vice President and Chief Information Officer and remains responsible for the company’s IT organization. He has over 25 years of experience in IT leadership, developing and implementing global mission-critical technologies and building processes and IT organizations to support them.