In the industrial sector, many companies have capital-intensive operations that mean investing a lot in assets up front — and not all companies manage to maximize the return on that investment.
Poor asset performance and efficiency result in poor ROI and hampers overall business performance. We often see this stem from issues such as poor utilization and unanticipated reliability issues, and it can result in significant profit margin erosion for the business.
To ensure companies are getting the most value from their assets, many businesses are using digital transformation and integrating operational data management. But digital transformation doesn’t have to mean a transformation away from your company vision and culture. Digital transformation is a powerful, multifaceted strategy that unlocks valuable insights from operational data, helping owner-operators to deploy precious capital to where it will make the most difference, and assist them in creating new processes that help increase revenue. There are four phases to designing a digital transformation that will optimize your data collection and analysis to optimize operations for greater profitability.
Planning Phase: Create a human-centric digital transformation
As the digital shift takes centre stage, it’s important not to lose sight of the essential human component. Digital transformation is disruptive and creating a culture or an organization that is ready to for this shift is a challenge. The process of digitalization in itself tends to focus on technology and infrastructure, and typically impacts a relatively small number of stakeholders within a company. For this reason, there is a risk of focusing too closely on the technical aspects and overlooking the human impacts and culture changes that will follow. The human component is extremely important, and sacrificing a company’s vison for efficiency could lead to long-term problems.
To successfully transform your operations — from mining to manufacturing — all digital solutions should produce a seamless and productive environment for all employees, delivered by harnessing advanced technologies that combine both operational and business intelligence into an integrated system.
Smart program management should engage with both the operations side and the business. Through broad consultation and process analysis, technical experts try to understand the client’s perspective by reviewing working processes with key business and operations stakeholders who have keen insights on integrating systems into a common data platform (whether cloud-based, virtual environment or a local/network approach). These platforms enable information exchange, and data can be aggregated and mined to use solutions such as machine learning and predictive analytics to eliminate recurring operational challenges. The goal is not to replace the owner in the transformation process and decision-making, but to accompany them and guide them to discover improvements that unlock key changes which allow them to achieve their vision.
Assessment Phase: Operational intelligence for business improvement
By studying the existing “as-is state” of a company’s operations, and better understanding the most critical KPI’s, transformation experts are able to map potential improvement targets to proven technology levers. This will be the basis for the “future state” of the company’s management systems. For example, by utilizing the Value Stream Mapping (VSM) approach, experts can develop a comprehensive as-is working process, which helps them find and identify inefficiencies, as well as proposed added-value processes and technologies. From order management, engineering, planning, production and manufacturing, to shipping, – each process must be analyzed with an understanding of the human-centric goals outlined in the planning phase.
The complex nature of this process means that an essential component is selecting a transformation expert with deep domain knowledge. With so many potential technologies, complex existing processes, and differing company cultures and corporate structures, there is no “one-size fits all” solution. Experts with global and broad experience can assist with industrial and manufacturing operations support, data collection and analysis to recommend design interventions, improve outcomes, and provide input for the business and safety and efficiency improvements for operations.
The Future State: Integrated Management Systems
The third phase is creating a vision for the company’s future operations and integrating the supporting systems that will deliver this future into a centralized, user-friendly platform. An integrated data platform can collect data from various instrumentation, automation systems, meters and sensors, and then analyze and identify ‘hotspots’ to bring focus to operational and safety improvements. In addition, the rapid advancement of technology (for example, Internet of Things advancements) and the lower cost of equipment offers a higher adoption rate, delivering faster results by integrating data analytics engines into traditional devices. The operational data metrics must be targeted and meaningful to inform improvements to operations, safety, employee, environmental, stakeholder and business performance (KPIs). An Integrated Management System provides the ability to provide a holistic picture of company performance through the intersection of planning, operations, maintenance, environmental, and safety through data analytics. Innovative ways of measuring and analyzing operational activity and mapping information into useful management dashboards is a priority. This requires innovative thinking to identify the overall quality of the operational “heartbeat” and map out where to focus improvement and capital expenditures.
An Integrated Management System roadmap is used to guide and advance projects. As we begin to adjust to an ever-increasing digital future, the rise of new process and monitoring technologies are the new standard within Industry 4.0. The adoption of Industry 4.0 allows for a focused problem-solving approach by narrowing down vast amounts of data from operations and identifying where corrective actions are needed to avoid unplanned downtime. These tools can also identify where potential investments may be required to connect all of the systems that underpin operations — such as raw material, mobility, supply chain, water, energy, infrastructure, standard operating procedures and employee training — to allow increased production with limited headcount.
Putting it all together: Unlocking data insights
Having vast amounts of data at one’s disposal does not necessarily add up to useful insights. In short, Big Data is not always Good Data. Therefore, the transformation advisor’s role is to gain meaningful insight by recognizing which segments of operations should be measured, what data is available to measure, what metrics can be accurately teased out of the data, and how to best present the information to be easily visualized and shared. It’s important to provide the capabilities to oversee production from the command centre onsite or remotely, and share this information in a consolidated way with management teams locally and at headquarters. Consolidating data into dashboards allows for much quicker turnaround for operational improvements and allows teams to see operational ‘outliers’ much quicker.
A bird’s-eye view of the operations with indicators for performance requires a cross-section of tools and approaches. No single approach or technique will fit all the diverse needs of data collection. The data collection effort can be broadly classified into two categories. First, traditional techniques that use existing technologies and are a snapshot in time (although there are certain exceptions); and second, new techniques that are predominantly digital in nature and collect data on a continuum.
On the traditional front, we envision deploying tools such as online platforms and in-person intercept surveys to capture behavioral changes and perceptions of the operations, maintenance, engineering and supply chain teams. New technologies in the form of cameras that collect, process and store continuous data streams can be deployed while maintaining personal anonymity. New devices and sensor systems use video as a sensor to capture and translate the video into a custom SQL database that can be linked in real time to custom dashboards that are accessible to operations and maintenance teams.
Through adequate planning, assessment and road mapping, an integrated management system can transform the way industrial companies look at their business, engage employees, operate efficiently and deliver products to customers. Essential to the transformation is creating a process that never forgets the human element, and one that draws on the skills and knowledge across industries and technologies. Essentially, it’s about making data work for you —not working for your data.