Building the Foundation

Continuous measures are one those factors that can be measured on an infinitely divisible scale; weight, height, time, temperature, pressure, ohms, money, energy, flow. You can't manage what you don’t measure.

Peter F. Drucker

Overview

In this chapter, you will learn how the South Texas refinery digital transformation team plans for implementation of the enterprise industrial data infrastructure (EIDI). Rather than focusing on the technology, the team reviews current workflows, how data is stored and consumed by refinery personnel, and how refinery operations can be continuously improved by addressing all functional areas, including safety and environmental issues, management reporting, and increasing visibility to all workers. The team will unveil their plans for how various refinery and corporate teams will access and share the information to improve operations and reduce costs. This chapter also introduces how other Proclndustries refineries and corporate support teams will ultimately benefit from an EIDI implementation.

The View from the Refinery Manager’s Office

The last month had been interesting at Proclndustries. The South Texas oil refinery, which Tom Jordan managed, suffered a major disruption that prompted the company to reexamine just about everything it does and how it does it. Tom was frustrated and upset about the refinery's inconsistent operations, but he kept thinking about the determination shown by Bill Roberts, the vice president of operations. Bill really wanted to improve plant operations and was willing to finance that initiative (see the box "An Operational Excellence Program"). Now Tom was on his way to a meeting called by Peter Argus, the new continuous-improvement manager at Proclndustries. Peter wanted to meet with the newly formed digital transformation team to begin their work: transforming the refinery culture to a data-driven practice (Duggan 2012; Miller 2014; Gonzalez 2014; Rogers 2016).

AN OPERATIONAL EXCELLENCE PROGRAM

An operational excellence program requires an agile, adaptive organization that helps people to be active, learning participants in the organization and, as a result, creates a culture of learning and continuous improvement. Specific steps to develop an operational excellence program include the following:

  • 1. Define common long-term goals for the enterprise.
  • 2. Articulate how systems and business processes enable people to simplify their jobs.
  • 3. Provide access to data to utilize data relevant to workers' individual roles and responsibilities.
  • 4. Ensure that people use a common set of definitions for the data they are interpreting.

After an earlier series of discussions with Peter, Tom realized that the oil refinery had data locked in legacy applications that people were not using. To unlock that data and add new capabilities, the company must take proactive steps:

  • • Install sensors on equipment to fill in missing data gaps.
  • • Upgrade systems to collect, process, and analyze the data.
  • • Implement new user interfaces and train people to use them.

These steps, when completed, would create a flow of data from equipment sensors in the refinery to the people making decisions about how best to run the refinery.

To date, Proclndustries had been averaging data from these isolated systems and storing it in relational databases for after-the-fact reports, which did not allow them to drill down and find root causes of problems. The operations department lacked real-time awareness of whether the refinery was running at optimal conditions or encountering problems.

Operations and production data was captured, averaged, and stored in software applications tailored for a specific function. Operations, engineering, maintenance, and the business planning department had their own data, which may not have matched what others had.

Tom felt the culture at Proclndustries represented another challenge. He knew employees did not believe the top executives had their best interests in mind. The perception was that senior management was out of touch with the realities of daily refinery work. Top management received reports based on accounting data, such as quantities produced and sold, but did not receive operational reports, such as daily operating costs and variances in planned and actual production levels.

Employees also believed that senior management did not want to spend money to remedy data systems. This perception appeared to be changing with Bill Roberts' support. Top executives did not appear to appreciate the additional work refinery staff had faced to comply with new regulatory requirements for environmental rules, occupational safety and health, and public utilities. If implementing a new digital data infrastructure system and applications meant asking staff to do more work, Tom was worried that he would have a management challenge on his hands.

Tom also recognized that the cultural challenges for this project went beyond how the refinery departments viewed management. Tom knew the refinery staff members were accustomed to their own way of doing things. Business processes that once worked well were now so entrenched that few could see that they had become obsolete.

To upgrade their current information systems and implement a modern system was a tall and complex order. Tom asked himself, what factors reduce complexity? He listed these factors as he prepared for the afternoon digital transformation team meeting:

  • • Universal standards that define business conditions and the data used to describe these conditions.
  • • A common platform for sharing real-time operations information to all personnel, empowering them to make quicker decisions.
  • • The ability to quickly analyze data and improve how the refinery is operated.
  • • A flexible information infrastructure allowing Proclndustries to manage future business changes.

Tom had been investigating operational intelligence and was planning to share some thoughts with Monica and Peter. His view was that operational intelligence would provide the ability to act on insights through manual or automated actions. Peter was creating a leadership vision for their digital transformation initiative.

 
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