A Plan for Successful Digital Transformation

Summary

Process manufacturing has become increasingly digitized and automated. But to achieve true digital transformation, a digitalization strategy must be built around the most important part of the system: the people who will use it.
 
Successful digital transformation requires technology solutions that empower workers rather than simply adding complexity to their workloads. It also requires a thoughtful change management strategy to increase worker acceptance. By putting the needs of people first, companies can leverage the power of technology to optimize processes, recover from disruptions more quickly and support the needs of a changing workforce.
 
For one major agrochemical company, digitalization solutions like digital shift handover and Smart Search reduced the time needed to troubleshoot problems, allowed them to optimize systems and processes, and ensured efficient transfer of knowledge between shifts, teams and areas of responsibility. A centralized knowledge management system will also help them retain valuable knowledge from experienced workers and get new workers up to speed faster.

Step 1: Knowledge capture 

An agrochemical plant generates thousands of data points every single day, from automated sensor data to inspection observations and shift notes. A centralized digital knowledge management platform can turn these data points into actionable information and usable knowledge. That requires capturing not just automated plant data such as fluid pressures or tank levels, but also the knowledge that exists inside the heads of operators, line supervisors, maintenance technicians and process engineers.
 
This hidden knowledge (sometimes called tacit knowledge) can make up a majority of knowledge in a plant, and it is critical to safe and effective operations. It is often hiding in plain sight in shift handover notes, inspection observations and ad hoc communication between employees. Digitizing these processes within a centralized plant process management (PPM) system allows this knowledge to be captured, retained and analyzed alongside automated sensor and equipment data.
 
For the agrochemical company, capturing tacit knowledge includes digitizing critical points of information transfer, such as shift handover. Capturing these transactions digitally also captures tacit knowledge and makes it explicit for other workers. Combining human-created information with automated sensor and equipment readings within a centralized PPM enables better troubleshooting, problem-solving and process optimization.

Step 2: Knowledge access 

Capturing knowledge is only the first step. It also must be made viable and usable for employees. A Smart Search system helps everyone find the information they need, when they need it, within the context of their specific roles.
 
Smart Search enabled the agrochemical company to fully realize the benefits of their digital shift handover and PPM systems. While their digital systems did a good job of capturing data such as shift handover notes, employees found it difficult to access the historical knowledge captured in the system. In other cases, entries were incomplete; for example, a solution to a production problem might be incompletely described, making it difficult to find through traditional search or hard to interpret and apply.
 
Artificial intelligence (AI) solved both problems. A Smart Search system enabled by AI can sift through historical data and find the most relevant information for the problem at hand. The AI system is able to understand the context of the search and surface relevant knowledge hiding in the data—even if entries are poorly labeled or incomplete. Employees can also query the system using natural human language. For example, a process engineer might ask, “Why is the product brown instead of gray?” Using natural language processing and machine learning, Smart Search can understand the question and look for historical precedents that might explain the anomaly. This makes it much more useful than traditional keyword search systems, which require users to know the precise search term to use and often return results that are not relevant to the user’s problem.
 
A Smart Search system for process manufacturing can be tuned to industry-specific or even plant-specific terminology, applications and scenarios. This allows the system to better understand user queries and return more relevant and useful results.
 
Since implementing the Smart Search system, the agrochemical company reports that the time users spend searching for the information they need has shrunk from several minutes to seconds. Employees also have better visibility into all of the historical knowledge in the PPM system, including specific solutions to production problems they are experiencing. The Smart Search system acts like a mentor, surfacing knowledge when it is needed to empower workers to do their jobs efficiently and effectively.

Step 3: Knowledge transfer and creation

At the agrochemical plant, digital tools like Smart Search have been well accepted by all users, from shop-floor operators to process engineers. A careful approach to change management has helped the company ensure broad acceptance and maximize the impact of their investment.
 
As people start using PPM and Smart Search, these tools enable knowledge transfer between people and teams and knowledge creation that results when data from disparate sources can be combined to generate new insights.
 
A centralized knowledge management platform helps to make tacit knowledge explicit. The SECI (Socialization, Externalization, Combination, Internalization) model of knowledge transfer provides a framework for thinking about how tacit and explicit knowledge in an organization are captured and converted into organizational knowledge. Digital tools can expedite the process, capturing information exchange between employees (socialization) and making tacit knowledge explicit (externalization). As workers synthesize this knowledge into their workflows (combination) and apply it independently (internalization), knowledge transfer is complete.
 
Knowledge management will be especially critical for process manufacturers as older, experienced workers retire. Up to 25% of the process manufacturing workforce could be eligible for retirement in the next five years, taking valuable tacit knowledge with them. An effective digital transformation strategy will empower the next generation of manufacturing workers and make plants safer, smarter and more resilient.