1
Early Equipment Management:
Delivering Capital Projects
Faster, Cheaper, Better
Most managers and engineers have had firsthand experience of capital projects that failed to live up to expectation when introduced and which needed significant attention during routine operation. The excess costs of these troublesome assets can be huge, and not just in terms of capital costs. One study of capital projects estimated that the additional attention needed to deal with troublesome assets and subsequent loss in performance can require around three years before asset performance is sufficient to begin the planned investment payback. This is a fairly widespread problem that has been with us for some time.
Based on publicly available data, Ross Henderson (1971)1 calculated the respective returns on invested capital of the Fortune 500 industrials. From the analysis, he concluded that there was “a massive failure among capital expenditure plans in North American industrial companies to provide the returns on investment which have been forecast or budgeted.” Studies by Pruitt and Gitman (1987)2 of Fortune 500 industrials showed that 80% of the respondents (121) admitted to having achieved lower returns than forecast, the worst results being investments in advanced technologies and new processes. This is not just a problem in larger organizations. More recent investigations in Cyprus by Lazaridis (2004)3 focused on small- and medium-sized companies. Of the 100 studied, only a third achieved the expected return on investment.
Get it right and the gains can be significant. An oil and gas extraction company investing in a floating platform to extract oil and gas from under the Atlantic estimated that the additional output produced by achieving the early equipment management (EEM) goal of “flawless operation from day one” was enough to recoup the total capital investment costs in the first year of operation.
This chapter summarizes the main themes of the book and how the recipe for capital project success combines hard/technical and soft/collaborative skills. It also highlights the role of project governance as a vehicle for improving internal management systems and for developing the operational capabilities needed for best-in-class business performance.
1.1 WHAT GOES WRONG?
Research into the causes of underachieving returns on investment indicates that systematic front-end engineering design (FEED) processes improve capital cost, timescale, and operational performance.4
However, this is not the full picture. Although FEED weaknesses are significant, they do not account for the following frequently occurring problems:
Conflicting views of what is needed
Difficulties in releasing resources
Lost opportunities to challenge and optimize design choices
Critical decisions delayed or not taken
Communication between project stakeholders interrupted or lost
These project governance issues frequently surface during projects, creating barriers to the delivery of results. In spite of this, they are specifically excluded from the scope of project management methodologies such as PRINCE 2 5 (Projects in Controlled Environments, version 2).
Table 1.1 describes the EEM project steps. Figure 1.1 explains how common pitfalls at each step contribute to poor project results.
TABLE 1.1
Capital Project Steps
| | Title | Content |
| 1 | Concept | Development of the project idea |
| 2 | High-level design | Approval of funding |
| 3 | Detailed design | Selection of vendors and detailed planning |
| 4 | Prefabrication procurement | Preparation of site and manufacture/procurement of equipment |
| 5 | Installation | Position and connect equipment |
| 6 | Commissioning | Set up and run equipment and validate process capability |
FIGURE 1.1
Traditional capital project delivery.
In this diagram, the lower curve illustrates the steps at which changes occur. Changes during steps 4 through 6 are in response to issues identified after the design is frozen in step 3. The upper curve shows the impact of those changes on total project costs. The shape of each curve is based on actual data captured by a machine tool manufacturer as a measure of project performance before the adoption of EEM principles and techniques.
1.1.1 Steps 1 and 2 before EEM
1.1.1.1 Change Curve
At the beginning of the project, attempts are made to obtain information to create a specification in detail.
1.1.1.2 Cost Curve
A cost estimate is made, including a contingency sum to cover unexpected costs.
1.1.2 Steps 3 and 4 before EEM
1.1.2.1 Change Curve
The focus of attention during procurement is on reducing cost (vendor margins) and ring-fencing risks. Changes after the award of contracts are resisted to avoid budget creep.
1.1.2.2 Cost Curve
Unexpected (though predictable) issues arise at factory acceptance testing (FAT) prior to the dispatch of the equipment from the manufacturer, which results in additional costs and potential budget overspend.
1.1.3 Steps 5 and 6 before EEM
1.1.3.1 Change Curve
Additional modifications are needed to deal with the issues identified at FAT. This includes compromises to operational performance, which reduces the expected performance gains.
1.1.3.2 Cost Curve
Budgets are squeezed to achieve savings in discretionary areas such as spare parts and training.
1.1.4 What Is Really Happening
As the project passes through each step, each decision has an impact on those made at later steps. At the earlier steps, detailed information is not generally available, so some decisions are better made later. Taking detailed decisions too soon increases the risk of error. That means that the design process is iterative rather than linear. Past decisions are revisited o...