The digital transformation is building systems that foster better performance and job satisfaction for employees across the organization. Here’s why.
Data generation is exploding at an exponential rate and increases the need for better management and real-time analytics. IIoT and edge computing are radically altering how and where data are collected, analyzed and stored. Consequently, an effective digital transformation strategy requires selecting the right metrics and standardizing the systems.1 Implementing a new culture on data and information management enables more efficient use of all organization resources. More importantly, employees are empowered; job performance improves when supported by real-time information.
Digitalization is a disruptor
Where to start is the most difficult question in defining a digital transformation program. Project teams and management can get lost in buzz terms, such as the cloud, big data, IIoT, AR, VR, AI and ML. The main driving force is implementing more efficient ways to openly access, analyze and apply real-time data to achieve company goals, as listed in Table 1.2
“How to implement the digital transformation” is the sticking point. IT, OT and operations groups must agree on the long-term strategy. The foundation (platform) of a digital transformation involves data strategy, cybersecurity, analytics, edge computing and the cloud. These factors shape the pathways to AI, ML and big-data analytics in order to achieve business imperatives (Table 1).
Table 1. Main goals for digital projects
| Market Environment | Imperative | Technology |
| Commodity prices and over supply | Capital efficiency | Cloud |
| Competition/consolidation | Compressed engineering, construction and design cycles | IIoT |
| Environment, quality, safety and health regulations | Operational efficiency and profitability | Big data |
| Generation shift (knowledge gap) | Asset availability/reliability evolution | Digital twin |
| Geopolitical uncertainties | Performance management and decision support | AI/ML |
| Pace of technology change | Workforce evolution and capability | AR/VR |
Worlds collide at the data edges
Data ownership must evolve from only plant or process users to the entire organization. The goal is distilling intelligence from collected data. Operations data have been protected from outside hackers through firewalls, air gaps and other methods. Unfortunately, such measures create silos of databases and information that hinder access by all organization users.
Table 2. Top technology challenges most likely to derail digitalization plans3
36% Technical skill gaps that prevent benefitting from the investment
27% Data sensitivity from increasing concerns over data and IP relative to privacy, data ownership and management
23% Lack of interoperability between protocols, components, products and systems
22% Security threats both in terms of present and emerging vulnerabilities
18% Handling data growth in amount and velocity as well as sense-making
18% Scalability roadblocks to accommodating growth without business or performance loss
IT and OT groups view data management very differently. IT focuses on cybersecurity, infrastructure and database management, especially for financial and reporting purposes. OT uses data as part of safety and automation systems to manage operations in a reliable and safe manner. Table 2 summarizes the major issues impeding digitalization projects.3 The greatest hurdle is the lack of in-house talent familiar with the ever-exploding wave of digital/IIoT advancements.
Getting started is the hardest part
A well-experienced, cross-sectional team is vital for success. The digitalization planning team must include experienced staff from IT, OT and operations. Human resources should have input on developing the digital transformation. Work processes and jobs will change as new technologies and information systems are adopted. Key consideration areas are:
- Identify the challenges in the present system architecture and plan for change. Innovative developments are occurring at a hyper rate.4
- Address the people, process and organizational issues along with the technology problems. Technology and people tasks will evolve as new developments become commercially available.5
- Build training and data literacy as part of the digital strategy. Skills upgrading will be needed to handle new tasks and systems.4 Software and smart devices are just tools used by properly trained employees.
- Consider the total cost of ownership of the hardware and software. Licensing, operation and maintenance costs can quickly exceed the original capital expenses over the service life of the solution.4
- Define the business case with the digital solution. The long-term view must identify savings through higher unit/equipment availability, profitability and sustainable operations to justify investment.5
A successful digital transformation involves adopting new work processes and creating efficiencies to attain business goals (Table 1). OT, IT and operation groups must embrace changes in:
- Technology (security/computing infrastructure)
- Labor processes (MH assets) and
- Capability (standard/flexible operating systems and work processes).
A new culture on data management and applications must be adopted by all stakeholders. The digital transformation not only changes the technologies people use, it also changes how people work together.3
Literature Cited
1Opsahi, David, “Four tips for pursuing digital transformation in manufacturing,” Forbes, August 6, 2020, https://www.forbes.com/sites/forbesbusinesscouncil/2020/08/06/four-tips-for-pursuing-digital-transformation-in-manufacturing/#56a0ab065099.
2AVEVA, Webisode 1: “Why you should consider an Edge-to-Enterprise strategy”, June 4, 2020, https://sw.aveva.com/webinars/edge-to-enterprise-strategy.
3 “Irene Petrick, Ph.D. and Faith McCreary, PhD, “Creating Lasting Value in the Age of AI+IoT – Futureproofing your Business”, December 2019, https://newsroom.intel.com//www/wp-content/uploads/sites/11/2019/12/futureproofing-your-business.pdf.
4Stratus Technologies, “10 Edge computing best practices,”https://www.stratus.com/apac/lp/edge/10-edge-computing-best-practices-ty/.
5Hill, Dick, “Are autonomous operations the future of process industries?,” July 23, 2020, https://www.arcweb.com/blog/autonomous-operations-future-process-industry.
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