5th Annual PPI Symposium Synopsis

The fifth annual Project Production Institute Symposium was held on 5-6 December 2018 in San Francisco.

Executives from a wide variety of companies such as The Boston Consulting Group, Chevron, ExxonMobil, Genentech, Google, Hess, IBM, McKinsey & Company, Merck, Microsoft, PG&E, Roche and Saudi Aramco, came together with researchers and academics from San Diego State University, Stanford, Texas A&M, and UC Berkeley to discuss how to resolve the global crisis affecting the engineering and construction industry through effective application of Project Production Management (PPM).

Presentations from the Symposium are available for PPI members here.

To kick off the event, Dr. Ram Shenoy, Project Production Institute’s (PPI) Executive Director introduced the Symposium, outlining topics of discussion for the two days of the Symposium. There were two separate tracks for attendees, with the first track covering an introduction to the PPM Technical Framework, supported by case examples presented by industry practitioners to illustrate to the audience how corporations are achieving better project performance through implementation of PPM. The second track explored Production System Optimization in more technical detail, illustrating how various tools developed over the last 20 years are used to define, design and optimize project production systems. The tracks were anchored by plenary talks and luncheon keynotes, particularly on the theme of how emerging digital technologies are already changing how PPM is implemented including the use of autonomous vehicles i.e. drones and IoT sensors.

Gary Fischer of Chevron Corporation was the first the plenary speaker. Fischer’s presentation opened the Symposium by sharing the story of his personal journey to transform Chevron’s capital project management system through the application of Project Production Management (PPM). According to Mr. Fischer, effective capital investment is the lifeblood of Chevron’s business. He observed that as one of the largest supermajors, Chevron’s Capital Project Management System included the state of the art in best practices in project management and delivery. Despite this, Chevron’s achieved project outcomes did not meet their expectations.

Fischer described the time invested in trying to understand the PPM framework, comparing the exercise with his personal hobby of fishing – “I got hooked on something big!” These efforts began to bear fruit with the implement of Project Production Control in the late stages of a large LNG project in Australia – Gorgon, specifically trains 2 and 3. Fischer described the results achieved on Gorgon, explaining the significant schedule compressions achieved over successive LNG trains, culminating in a best-in-class performance in the last train.

From the results achieved on Gorgon, Fischer described parts of his personal journey in tracing the performance achieved with PPM in past landmark capital projects, such as Heathrow Terminal 5. These studies helped him finally realize the difference between PPM and other conventional project management practices. He proceeded to describe how the PPM perspective educated him to “see things through different eyes” – looking around the activities of a project and seeing WIP building up; using a new vocabulary of throughput, capacity and cycle-time among others; and a host of insights learned from reference books such as Factory Physics.

Fischer explained his journey was one of many being undertaken at Chevron, and proceeded to outline Chevron’s roadmap of adopting PPM across the breadth of its capital project portfolio. He stated that Chevron had demonstrated the feasibility of Project Production Control to close a significant performance gap in the industry, and outlined the steps of adopting PPM enterprise-wide. Fischer closed with an aspirational goal for realizing the full potential of PPM, to get to Production Engineering where the PPM is implemented across the full project value stream so as to design to build efficiently. He concluded paraphrasing that Chevron used to focus on “what”, “who” and “when – but now PPM was more importantly getting them to focus on “how”.

Gary Fischer’s talk was a call to arms to the audience on embracing the potential of PPM. It was followed by Matthew Parsons’ presentation, which was a provocative challenge outlining the limitations of the status quo.

Matthew Parsons, Partner and Managing Director at The Boston Consulting Group, specializing in Energy and Operations areas followed Fischer with a presentation describing the unintended consequences of current best practices of project management. He categorized consequences in terms of their impact on the business, design and execution elements of projects.

Among the most severe business consequence was the need to make capital and other resource commitments far earlier than needed because of inordinate lead times and other contingencies that required fixing project scope and requirements earlier than needed. This results in an unnecessary buildup of excessive WIP. For project design, the consequences were design inflexibility and higher costs of change from the loss of ability to make decisions in natural cadence with the development of a project.

Unanticipated work, out-of-sequence work and cost associated with poorly thought out modularization decisions whereby the longer lead times necessitated by off-site fabrication frequently added unintended delays and costs, which frequently could not be recovered from.

He reviewed the original technical assumptions underlying the well-known fixed time-cost tradeoff, observing it did not hold if variability was reduced.

Finally, he described how project execution suffered in a variety of ways including rework, and the associated work and costs of holding inventory longer than planned and managing for obsolescence and theft.

Parsons concluded with a quick history of advances in the thinking and implementation of supply chain practices and a call to action to train a new generation of capital project leaders rather than capital project administrators.

He used this context to frame the following question for the audience “how will the emerging trends of Artificial Intelligence, Machine Learning, Automation and Internet-of-Things affect the engineering and construction industry”.

Dr. Jha talked about fire as the most important innovation. It created more time for humans to do other things, allowing humans to develop the brain, then progress through the wheel, agriculture, written language, printing press, industrial rev/trans/mass manufacturing, which led to globalization the transistor leads to miniaturization and microchip which then led to internet and mobile. Dr. Jha went on to outline four key messages. First, while technologies kill jobs, they ultimately have created more new jobs than they have killed. Second, regardless of new technology innovation, the demand for leisure and healthcare never goes down – it always grows. Third, these two previous trends can be used to identify a number of big industries of the future. For the fourth, Dr. Jha concluded by drawing a number of observations for the audience on implications for them, explaining.

Within the talk, Dr. Jha delivered many pithy observations, such as, “the future is here…. it’s just not evenly distributed.” He also spent time discussing “How did we get here?” Dr. Jha talked about the major technological evolutions over time and linked them to the digital revolution. He observed that globalization was one of the most profound accelerants of innovation and can’t really be stopped except by war, citing World Wars 1 and II as the only obstacles to the historical advance of globalization over the last two thousand years.

Dr. Jha went to talk about “Where are we now?” He described the state of the art in pattern recognition, noting that 60% of human brain power is about recognizing patterns, and explained that computers are now superior to humans in speed and accuracy in certain types of image recognition. He stated that a truly disrupting trend is the generation of data with the Internet of Things (IoT) and then using Artificial Intelligence (AI) to process the data.

Dr. Jha encapsulated this stating “It’s not about new algorithms it’s about computers being able to do things faster than our brains. Which then allows humans to do other things. AI could train your hardware machines vs using a software engineer…frees the software engineer to do other things.”

Another example given by Dr. Jha was that of 5G as the next advance in telecommunications infrastructure. 5G will require 10-20x more capital expenditure than the previous generation of wireless telecommunications infrastructure, 4G. With that increased expenditure comes increased complexity of infrastructure deployment, as the new infrastructure of 5G has to overlay the existing 4G infrastructure in dense urban environments.

Dr. Jha noted the continuing shift move away from voice being important as it’s now all about data. He connected 5G with the proliferation of data centers requiring high bandwidth connections e.g. 30 terabytes/sec between cluster data.

Dr. Jha went on to discuss energy consumption as a marker for economic growth, noting that population growth and the aspirations of the developing world to reach material standards of living comparable with the US were an assurance of continued energy demand and consumption, concluding on the huge infrastructure opportunity over the next few decades. He also noted several other industries of the future resulting from these macrotrend.

Following Dr. Jha’s keynote, the 2018 PPI Technical Achievement award was presented to Professor Martin Fischer, Fifth Kumagai Professor of Stanford University’s School of Engineering, and Director of the Stanford University Center for Integrated Facility Engineering. The Award was presented by Dr. Mike Williams, Director of Academic Relations at the Project Production Institute, and Todd Zabelle, Founder & CEO of Strategic Project Solutions Inc. – the full announcement is available on the PPI website.

Natarajan told the story about the development of the Disney “Fitbit”, emphasizing the key is not about the technology, it’s about improving the customer experience. To enhance the customer experience requires a data rich supply chain. The question is how to manage your assets digitally and better. This applies to any industry, not just commerce but also oil and gas.

He went on to list the problems in current supply chains:

1. Fragmented data, system silos-data not captured or instrumented

2. Pull vs push: mostly transactional RFID/barcode provide spotty coverage

3. No “edge” intelligence (bring the cloud to the edge): infrastructure to support the autonomic process of the future, connected products and assets between and across the organization

4. Variances and disruption cost billions in value loss

Natarajan said the opportunity is to create a “talking” supply chain- real time tracking-bring assets and workflows into real-time visibility for real-time visibility.

A particular theme throughout Professor Kaminsky’s talk was on the role of robustness in inventory vs timeliness tradeoffs in project delivery. The motivation for the theme was the symptom of “too much inventory” in multiple interviews conducted in 2017 by Jabbari and Professor Kaminsky and reported in the 2017 Symposium. Those interviews think that either the tools available aren’t robust and effective enough, or the people using the tools need more training to use them effectively. Professor Kaminsky then went to outline a number of simulation scenarios to make the case that there was huge loss of value in the way inventory is procured and managed in today’s capital project supply chains. He highlighted this as being due to an insufficient appreciation of the need for robustness – defined as a lack of sensitivity to variability and unforeseen disruptions. The progression of examples shown by Professor Kaminsky showed that consideration of robustness lowers project expected completion times, especially if there is extra flexibility available in resources and fewer constraints. This is generally counterintuitive because the drive to improve efficiency and productivity metrics generally contributes to LACK of robustness, with huge consequences and exposure when variability strikes. Early efforts indicate that the amount of inventory on construction sites and in the associated supply chains is far beyond what is needed.

The lunch keynote of the second day was given by Dr. Ben Amaba of IBM. He discussed a variety of emerging digital technologies to make a number of points about their successful adoption and implementation. Among the messages he conveyed to the audience:

• Project Production Management is a golden nugget, one of a few frameworks to intelligently organize digital implementation

• Validation (Why), Verification (How) are essential to deciding and executing the What – whether it be Configuration, Artificial Intelligence, Internet of Things, Robotic Process Automation.

Dr Amaba’s point was that companies generally focus too much on the What, because new technology is the shiny new thing. He went through a number of IBM’s past experiences and lessons learned to demonstrate that it is really important to understand why companies want data and how the data will be used before the technology or tool is selected. Among the challenges shared by Dr. Amaba was IBM’s realization that when Watson had a slower uptake than hoped for, they understood that the perception of AI as being untrustworthy and the need for a greater emphasis on the customer experience – in other words a greater emphasis on the Why and Who.

Dr. Amaba concluded with describing IBM’s more recent successes from these lessons, such as with the rollout of Blockchain. He talked about the value realized by network orchestrators through greater connectivity and its evolution into the platform that offers transparency to multiple participants, creating the trust needed for AI to perform.

Dr. Amaba closed his talk with some high-level comments about competitive threats coming from any quarter outside an industry – today a company’s future competitors may not be its current ones but may not exist or may come from outside the industry. By way of example, he speculated whether companies such as Amazon, Microsoft, Google and Facebook might choose to enter the energy industry with a host of different capabilities from today’s incumbents.

Professor Martin Fischer of Stanford University gave the final keynote of the second day. Professor Fischer continued a sequence started by Dr. Sanjay Jha, and continued by Shekar Natarajan, Professor Phil Kaminsky and Dr. Ben Amaba, describing some of the work of his research group, but within the context of the Operations Science principles the audience had heard about throughout the two days of the Symposium. He affirmed that everybody wanted to execute their projects fast and at low cost. He then asked how many people thought about whether the practices they introduced into their projects actually reduced or increased variability and proceeded to explore the impact of a set of emerging technologies on this question. He examined questions of work sequencing and the impact of different operations sequences on cycle time, quality and the impact on variability, showing the results on cost and schedule in a number of examples. He reinforced a theme introduced by Professor Kaminsky on the value and impact of computer simulation to explore millions and billions of scenarios where before humans could practically consider at most 10-20. Professor Fischer went through a number of examples where exploring broad sets of scenarios identified situations and circumstances to improve upon existing construction practice finding solutions and paths that humans on their own would almost certainly never identify. He finished by remarking that a materials revolution was taking place not far behind the digital revolution, observing it was better to have worked out the digital revolution to take best advantage of the impending novel materials that are coming to capital projects.

Professor Fischer closed with a discussion of the historical cooperation between Stanford University, the Project Production Institute and Strategic Project Solutions in developing and offering the Virtual Design and Construction course over a number of years. He explained the logical evolution was now to retire that course, and to offer instead a joint Stanford University CIFE-PPI certificate course in Project Production Management. The last VDC courses will be offered in Q1 2019, after which Stanford University CIFE and PPI will be launching and offering a certificate course in PPM in 2019 and beyond.

The first day of Track one was an Introduction to the Project Production Management Technical Framework, similar to ones given in years past. It consisted of an instructional seminar led by Dr. James Choo, Member of PPI’s Technical Committee, and Chief Technical Officer of Strategic Project Solutions Inc., and Dr. Ram Shenoy, Executive Director of PPI. The day included a case problem and a discussion of the historical evolution of project management framework, using the 3 Eras framework. Following that, Dr. Choo and Dr. Shenoy gave tutorial introductions to the basic operations science relationships governing production systems. Project Production Management was introduced as offering visibility on a few additional levers traditionally highlighted in conventional project management – variability, WIP and capacity. The Day’s session concluded with a discussion of several examples.

The second day of Track 1 comprised of industry practitioners describing real-life examples of application. Jennifer Weitzel, General Manager of Microsoft’s Global Data Center Program, then discussed select challenges in optimizing the supply flows in the Microsoft global data center program. She started by describing the business drivers for growth in data center construction across the entire industry of cloud service providers and data center owners. A consequence of this growth is that the available capacity of labor and skills available in certain geographic regions to support the construction of data centers is less than demand. As such, Weitzel outlined some steps Microsoft has taken to manage those challenges in terms of reducing customization in its base designs, identifying, qualifying and securing preferred supplier capacity, establishing its demand forecast and actively tracking critical supply flows. She illustrated some of these steps, showing a sample equipment supply network and outlined moves away from single-sourced custom equipment toward multiple sourced, standardized designs. She concluded by showing some early results achieved on lead-time reductions and improvements in overall cycle times.

Creech and Nehring then gave an overview of their implementation and results achieved. Among the topics they covered:

• Creating a standard value stream and managing it as a production system

• The requirement for flexibility: activity has to flex with rig count with higher or lower oil, with winter weather, with requests for schedule acceleration

• When variability goes up, so do inventory and WIP while capacity decreases.

• All work activities are governed by Little’s Law and Cycle Time Formula.

The Hess view is that traditional Project Management is enhanced by Project Production Management. They cited several practical examples of managing variability. For example, due to winter weather, they decided to minimize building of pads during the winter – so rather than build for 12 months, they are building them for 7 months of the year. In some years they had to shorten even further. The key principle they emphasized was to build an intentional buffer with all work to be completed so that the rig can continue to drill through the winter.

Hess also attacked drilling cycle times. Creech and Nehring described a reduction from 16 to 8 days from 2016 to 2021 (currently at 11.7). This accomplishment required them to tighten the planning belts and increase WIP and buffer upstream of drilling to support increased throughput.

They also had to prepare the downstream – once the well was ready to create a smooth handoff, so that overall system throughput was preserved.

They also discussed how Hess’ PPM/well factory approach has greatly improved relationships with their contractors, with contractors are more self-sufficient and motivated to learn. Safety has also improved. They are in the top quartile of safety performance vs other operators. In addition, drilling cycle time has been reduced by 70%, completion costs have been reduced by 60% and development costs by 70%. They are drilling the same number of wells with half the number of rigs.

Creech and Nehring were then joined by Weitzel for a joint question and answer question that was universally acclaimed by the audience as one of the highlights of the track. Despite the apparent difference in the two case studies presented by Weitzel of Microsoft and Nehring and Creech of Hess, the audience appreciated and remarked upon the many commonalities between the two cases, and the similarities of the PPM technical framework applied in each case. Among the common themes – understanding the variability; taking measures to control the level of WIP; the use of appropriate buffers to manage variability and WIP.

Track 1 concluded with two presentations from Chevron given by Jim Craig and Craig Evans. Jim Craig began describing Chevron’s activities in extending the application of PPM beyond capital project execution into Front End Engineering. After a brief recap of Chevron’s implementation of Project Production Control in capital project execution, Craig described the motivation into the Front-End Engineering and Design stages of capital projects. A major contrast he highlighted was that these activities were highly knowledge work intensive, very different from the craft work-intensive activities of construction and installation. Craig described some of the challenges and benefits achieved from implementing Project Production Control in the Engineering and Design phases of capital projects. Among the benefits he observed:

• Standard processes led to greater alignment on work execution

• Greater focus achieved by the team on the “Right work” to advance the project

• A unified set of metrics and analytics for everybody to understand the true status of the project

• All of the above culminating in cycle time reduction through optimizing execution of the engineering and design activities.

Jim Craig also observed that in the long run, as PPM is fully adopted, it logically pointed to Chevron stopping some other practices born of “Era 1” and “Era 2” thinking – he could envisage some weekly engineering reports and traditional project controls reports being rendered obsolete as the organization embraced PPM.

Jim Craig concluded by noting that the future is modeling Projects as Production Systems from start to finish, starting with project definition. It will take leadership and perseverance to realize this vision.

Craig Evans followed Jim Craig with a presentation showing the implementation of PPM on a large Chevron project in Kazakhstan. He started with a quote of Professor Brian Cox:

“Science is the art of looking at the evidence and removing your prejudice”

He pithily turned it out around to describe the challenges he has encountered in overcoming some entrenched attitudes in conventional project management:

“… Ignoring the scientific evidence to continue supporting their prejudice”

Evans went on to explain that ignoring the scientific foundations of operations science and PPM was somewhat akin to believing in a flat Earth.

He then went on to describe the implementation of Project Production Management in various aspects of project execution in the capital project he is responsible for. PPM has been implemented using three business processes: production scheduling, production planning and continuous improvement.

Evans outlined how the population was trained to look at project activities from an Operations Science perspective, such as recognizing and understanding the buildup of WIP as a consequence of project decisions. Craig illustrated an example of WIP build up showing a photograph of a work-site, commenting on how the photo showed WIP build up in different locations as a consequence of earlier project decisions. He went on to describe some of the benefits realized by Chevron so far. In engineering, he outlined improvements in resource planning and the benefits standard processes brought in managing variability, including identifying sources of variability that were previously unidentified.

All of this has resulted in improvements in throughput and reductions in WIP. Evans concluded by explaining that what has been achieved is only the beginning – he outlined a roadmap of rolling out PPM through other project activities such as in supply flows and to other craft installations.

Track 2 was for participants who already have a foundation and baseline understanding of Project Production Management and focused on how to use Operations Science to model, control and optimize Project Production Systems.

The Production System Optimization Track addressed the challenges of better project delivery with presentations, breakouts, case studies, games, simulations, shared experience and good humor. Attendees from companies such as Chevron, Hess, McKinsey, BCG and Microsoft participated in discussions from Ed Pound, Mark Spearman PhD and Todd Zabelle, and also broke into small groups to discuss topics such as their company’s current project selection criteria and sources of variability in their projects, and how this silo vs system thinking has been disconnected from actual business metrics and workface progress.

What was clear throughout is that current project management approaches are not working, and that a better framework is needed to support project delivery efforts. Owners and contractors typically do not have a good understanding of their overall project delivery design. There is high frequency of local optimization which leads to increased queue times, increased cost, schedule misses and safety incidents.

This was illustrated beautifully with a newly developed dice game. It illustrated the major gaps in Era 1 and Era 2 thinking on project scheduling and control, providing clues to filling those gaps. The takeaway was that in order to guarantee that the project would be delivered on time, it is not necessary that each module be delivered on time. Moreover, it became clear that “silo thinking” was a key cause of long cycle times.

Attendees also explored how to optimize Production Systems using an Operation Science framework. They learned that there are only three buffers to mitigate the effects of variability and these are inventory (modules finish early), time (modules finish late), and extra capacity (which reduces both the inventory and time buffers). They also learned Little’s Law relating the rate of progress with WIP and cycle time. One takeaway was that WIP is “visible cycle time” and that when WIP goes up, cycle time will follow.

The discussion then went to defining, modeling, analyzing, and optimizing the production system using analytical and discrete event simulation models. Using an analytical model, Spearman and Pound showed how one can discover problems in a production system design before it goes into operation. They also demonstrated how a project can come in quicker with lower cost, without changing anything except how the Project Production System is controlled. However, before you can do a good job of controlling the system, you need to optimize it first. Here they demonstrated the Value Modeler that combined elements of analytical and discrete event models accompanied by an optimization engine. The Value Modeler selects the optimal number of each resource to maximize the profitability of the entire project by considering cash flow and cost per unit.

The track had two key messages:

Why Production Systems Optimization? Current approaches to project management are deeply flawed and have led to repeated failures to meet project budget and schedule targets. Production System Optimization provides the Operations Science to correct those flaws and deliver projects on time, with less cost and cash. It makes project delivery easier and projects more profitable using a comprehensive repeatable framework for more predictable project outcomes.

What is Production Systems Optimization? Mapping the process in sufficient detail to be able to model, simulate and predict its behavior. A project schedule is NOT a process map. Operations Science drives the data requirements for the map. It allows us to build analytical models or discrete-event simulation models to understand, design and optimize project delivery.

The Symposium concluded with PPI Executive Director Dr. Ram Shenoy presenting a synopsis of key messages from the presentations of the day. He described the Institute’s calendar of events for 2019 and reminded the audience of the different Institute resources available from the PPI website, such as the glossary and technical journals.

Get the word out to your teams to join the institute and save the date for the 2019 Symposium on 03 – 04 December 2019 at the Four Seasons in San Francisco.