Overview

Simudyne Introduction (PDF) - This white paper includes overviews with Return on Investment for a number of projects that leverage the algorithms that underpin our platform.

Statoil

Statoil Gas Flow Value Chain Simulation

Statoil simulates the gas flow value chain – the flow of natural gas from the production site, through the refineries and into the various markets – to understand, compare and select the optimal market and production opportunities. Statoil’s gas flow value chain simulation allows them to quickly analyze and compare many different scenarios. After an initial screening of thousands of scenarios, they can come down to a “short-list” of 200 different scenarios. By running these scenarios through the simulation, they narrow the number of interesting alternatives to a fraction of these, leaving the management team with 40-50 highly interesting market and production scenarios. More detailed simulation models are then used to optimize and calibrate the various scenarios, depending on the given market situation, and pave the ground for the final decision. Simulations save Statoil millions, by allowing them to focus on the right opportunities, not all opportunities.

Statoil Nordic Pricing Simulation

Statoil's long term scenario & pricing simulation model for the Nordic region lets the user set parameters for demand, capacities, marginal operational costs etc for six electricity areas in the northern part of Europe. The simulation calculates the prices in the different areas, and the need of electricity transfer between the areas. All in averages over one month. By looking at the output values, traders in the market may easier decide when, and how much, to buy and sell to and from the different operators.

Statoil Mobile Oilrigs Simulation

Simulation is also used by Statoil to manage their fleet of mobile oilrigs so they can guarantee the availability of platforms and maximize revenues. The simulation enables projections of demand for rigs using a model of the lifecycle of an oil field from exploratory drilling to the process of taking a field off-line. Analysts can input costs and revenues to produce long term financial statements under various policies. Management can conduct ‘what-if’ analysis on a range of possible futures based on the current state of their mobile fleet of rigs. The simulation supports a variety of future oil price scenarios (high, medium, collapse) so management can find an acceptable rig management policy under these assumptions.

Statoil's Kogen Investment Simulation

The Kogen model simulates possible consequences of building a power plant fueled by waste gasses from a methanol refinery. The model is used to perform complex sensitivity analysis around technical uncertainties and market risk. In addition, the model is used to determine the optimal ownership structure and operational model for the project.

Large Energy Company

Simulation was used to help their energy traders understand the dynamics underlying energy pricing, given the current states of energy supply and demand within the Northern European energy sector. They built a simulation to represent the flows of energy between regions as supply and demand varies. The system included the type of power plant used to produce the energy and takes into account seasonal weather variations and the cyclic economic factors that influence the supply and demand of energy. Using a range of economic models, they derive the average energy prices in the various regions, given the behaviors of all the major players in the Northern Europe energy market. The simulation resulted in energy traders making more certain decisions on buying and selling energy in the various regions. The simulation further supports the running of possible future scenarios so that contingency plans were created to quickly profit from future crises.

Energy Company

Output from Landmark’s VIP software is a key input into this strategy simulation as it provides the estimates for future oil/condensate/gas production under different development options and subsurface uncertainties. Asset managers also enter business decisions (e.g. production mode, evacuation type, gas disposal method), market uncertainties (e.g. customer demand, product price) and cost structures for each scenario. The simulation system projects figures relating to production profiles, pipeline capacity, wells, gathering centers, operating/capital expenses and other financial metrics.

BP

BP Amoco Investment Simulation

Simulation allowed BP Amoco to make faster investment decisions. They used the power of simulation to examine the economic results of upstream decisions in exploration & development and in downstream initiatives such as building new plants. The simulation allowed them to identify an investment strategy that returns the highest economic value for the business. Their teams can create coherent projections of gas production, capital and operating expenses and other financial figures. They can conduct evaluations of new high-level production profiles in hours, not weeks. The simulation helped Amoco management work from a shared set of assumptions to discover and take advantage of previously unseen opportunities. The simulation was integrated with business data from several internal sources to give a realistic setting for scenario analysis.

BP Trinidad Strategic Planning Simulation

The Trinidad Strategic Planning Simulation allowed BP Amoco planners to examine the economic results of decisions in both upstream areas (exploration, development) and new downstream initiatives (LNG plant). Projections on gas production, capital and operating expenses, and other financial figures provide the means to find an investment strategy with the highest economic value for the Trinidad gas business. Prior to introduction of simulation, planners wishing to examine the overall economic value of a new future scenario needed to spend several weeks manipulating a diverse set of spreadsheets. With this simulation, planners can create a new high-level production profile and view economic results in just a few hours.

BP North Sea Projects Simulations

Their Strategic Planning Simulation is used in their North Sea projects to clarify their many complex business processes involving numerous platforms, pipelines and oil in a complex array of underground reservoirs. The simulation tool provides an overview of the complex projects and simplifies key decision-making processes.

Chevron

Chevron used simulation to optimize the processing and marketing of gas-derived products in Nigeria. They created a simulation to run scenarios of investment options over a 25-year planning horizon. The simulation allowed them to select and prioritize sources of gas supply using different technologies to maximize gas revenues. They were able to define policies for the disposal of excess gas. The simulation supported testing of management assumptions on government regulations, competitive pressures and prices.

BHP Billiton

BHP Billiton is the world's largest diversified resources company. BHP developed a Strategic Value Chain management simulation to allow the organization to input market information and demand, and cascade this demand down the value chain to identify how and where resources needed to be drawn from, and to what extent the organization was required to restructure its distribution. At the same time, the simulation allows management to explore with various strategic policies, like adding a new mine, adding a new alloy plant, adding and/or changing the distribution lines, etc. The results of the simulation have been very good, and it is today used across the organization within all the main segments of the value chain, as well as for a top-level management view on the entire value chain.

  • Screen Shot - Overview of the BHP Value Chain - The red lines represent flow of material from Mines to Alloy Plants, to the Logistical network and into the Markets. This simplified picture contains a highly complex flow of hundreds of product mixes and variations, but at this level, the top-level management can get the quick aggregated view they need. Exploration options at this level can for instance be to add a “New Mine”, a “New Converter” or a “New Alloy Plant”, etc.The Blue lines represent the flow of information from the markets, back to the two main production units (Mines and Alloy Plants). As you see, the system can select its start and stop times (bottom left) to allow management to explore within different time periods. The model can also be fed various raw-data, either live data from APO (bottom right), or simulated data from the simulation model.
  • Screen Shot - Markets - If you look closely at the “tabs” at the top of the window, you see to the far left “Input”. Every view (Overview, Finance, Markets, Logistics, Plants and Mines) has four different modes: Input, Output, Description and Setup. Viewing the markets tab, we see that we are in input mode, currently looking at the prices for Alloy, having selected one of the sub-products. The prices may be explored in all markets, or certain sub-markets. In this case we have selected Eastern Europe, products distributed from a certain Plant, and a specific category of products (78HCFeMn). The model stores all variations of the products, with all granularities. When the end-user operates the system, however, we try to provide only the relevant information, and avoid “flooding” the end-user with too many parameters at the same time.
  • Screen Shot - Finance - The screen shot shows input parameters for Finance. The diagram indicates the variable costs during the time period of the simulation. Since this is an input, the user may click on each of the bars and modify the value of a variable by moving the bar up or down. This way, alternative values may be explored.
  • Screen Shot - Output Reports - When the user selects Output (reporting) and Overview, a very simple and clear report is presented, containing all the relevant key volumes, market information and financial information. Data is presented as “Budget”, “Actual” and “Simulated”. This Budget and Actual data is stored in the SAP data warehouse, retrieved through the seamless SAP links, and presented in parallel with the Simulated data. The end user can now drill down on any area of specific interest, or select various reports for presentation purposes (like EBIT Waterfall Chart, MTU Waterfall Chart, etc.).
  • Screen Shot - EBIT Waterfall Charts - When the user selects Output (reporting) and Overview, a very simple and clear report is presented, containing all the relevant key volumes, market information and financial information. Data is presented as “Budget”, “Actual” and “Simulated”. This Budget and Actual data is stored in the SAP data warehouse, retrieved through the seamless SAP links, and presented in parallel with the Simulated data. The end user can now drill down on any area of specific interest, or select various reports for presentation purposes (like EBIT Waterfall Chart, MTU Waterfall Chart, etc.). To illustrate some of the possibilities, an example of an EBIT Breakdown at overall levels is presented.
  • Screen Shot - Plant Production Charts - Finally, it all boils down to what the requirements are for production of different units and products at various times. As an output of the system, the simulator provides production profiles as shown in the screen shot, as input to the production units. The same reports go to the distribution centers, for identification of the distribution flows.

Procter & Gamble

Procter & Gamble is a $38 billion corporation that controls and consumes a great many assets and raw materials, processes them along parallel and intersecting pathways, and produces a large variety of wares that it then distributes all over the world. Five simulations of the P&G supply chain were developed by colleagues from Bios Group (now defunct) and thousands of scenarios under different settings and conditions were run. As a result of these simulations, new policies were implemented that saved P&G $300 million in the first year.

Unilever

Unilever is one of the world's leading suppliers of fast moving consumer goods across food, home and personal product categories. Unilever uses simulation for better foresight into which marketing initiatives, investments and legal commitments will yield the greatest ROI. Simulations allow them to exploit years of market research data by connecting historical brand performance, consumer attitudinal insights and competitor intelligence to provide unsurpassed control over the distribution and utilization of key resources. In Unilever’s case, simulation ROI is measured in billions of dollars of additional revenues for the company.

FMCG

FMCG (name changed to protect identity) is a provider of fast moving consumer goods, including food, home and personal products. Their products are recognized globally and are distributed in more than 30 countries. They use simulation to test and define the marketing initiatives that they should execute, and then appropriately time these marketing initiatives. The simulations also allow them to quantify the value of their customers such as Wal Mart and Tesco as well as the consumers who visit these stores. Furthermore, simulation’s support of the intangibles of marketing enables FMCG to identify and track customer and consumer data on attitudes, behaviors and product loyalty – all of which enhances FMCG’s ability to compete against rivals. For an Eastern European fabric conditioner, FMCG used simulation to answer three key questions:

  1. How are consumers purchasing decisions dependent on their placement along the Brand Experience Cycle?
  2. What can we do to move people up the Brand Experience Cycle to become loyal users of FMCG’s products?
  3. Should we launch the fabric conditioner in this county?
  • Screen Shot - Opening screen
  • Screen Shot - Pumping people from Unaware to Aware of the company's products .
  • Screen Shot - Brand managers and financial analysts can adjust a number of parameters on the fly to assess thre impact on a variety of scenarios
  • Screen Shot - Pro Forma P&L created for each scenario

International Bank

During this large bank’s transition from branch-only to branch and Internet service delivery this international bank decided to compare simulation with traditional spreadsheet analysis. Two studies were simultaneously commissioned. The first, conducted by one of the world’s top strategy firms, cost £1.2 million, took eight months and gave the wrong answer (with the benefit of hindsight). The other project, conducted by simulation experts, cost £500 thousand, took four months and gave the right answer. Actionable strategies from the simulation were derived faster, at lower cost and with better results than traditional analysis.

Global Telecommunications Company

A global telco recognized that it was failing to meet delivery times for customers subscribing to its large range of products and services (these varied from traditional voice products through to data and VOIP provision). A simulation was developed to solve this issue. The simulation allowed the telecom to explore a range of strategic issues. The simulation represented the whole provisioning business from receipt of an order to final test and sign off. It drew on a huge range of data including: sales tracking; training programs; work flow analysis; staff productivity collected through corporate mainframe systems; interviews and business plans; demand forecast for services. The simulation could also exploit earlier workflow studies carried out within the organization. The simulation enabled them to identify key pinch points in their provisioning system. Based on simulated staff utilization and order backlogs within each job area, their recruitment and redeployment strategies could be assessed while recognizing the attendant training requirements and impact of staff experience on performance. The outputs from the simulation were a major contribution to developing the strategic plan for the business.

Global Pharmaceuticals Company

A major multinational pharmaceutical firm wished to communicate new strategies regarding the drug discovery process to its internal research staff. They used a three-day workshop based around a hands-on simulation exercise. One of the key issues that this workshop focused on was a portfolio approach to drug discovery. In the past, researchers had been rewarded for pioneering efforts on individual drugs. Company management wished to shift the focus to a portfolio approach, in which it was acceptable to terminate projects with a low probability of success in favor of other more likely targets. After a series of pilots this workshop became part of the standard training program within this company. All research staff above a certain level went through this program, along with all relevant new hires.

Training Group Defence Agency

The Training Group Defence Agency in the United Kingdom operates a fleet of more than 400 aircraft, employs 5900 military and civilian personnel, recruits Royal Air Force personnel and provides flying training to the Royal Air Force, Royal Navy and Army personnel. TGDA developed a simulation used by all bases in the United Kingdom that allows them to holistically plan and assign resources like instructors, aircraft and operational personnel at the right base, at the right time for their particular training - whether it's a fast jet, a helicopter or multi-engine aircraft. Simulations allow TGDA to forecast more accurately and quickly run scenarios in a synthetic environment where mistakes are more tolerated than in the real world. The simulation has realized gains for the UK Ministry of Defence in staffing requirements and resource allocation, in more effective management of seasonal variations in demand and in more meaningful communication between TGDA and training stations. More information available on the Simulation Science blog.

USA DoD and UK MoD

The Operating and Support Cost Analysis Model (OSCAM) is a joint US/UK program providing rapid assessments of the O&S costs of high cost capital assets and their component systems. The simulation helps defense ministries and industry plan the cost of complex military systems. OSCAM represents business processes using a simulation. An intuitive interface has been created to enable the management of large data sets and to assist with strategic ‘what if?’ analysis. Over 300 people have been trained in its use and it is being used on several high profile acquisition programs.  

UK MoD

A simulation was created to populate the Transition and Sustainability Simulation for UK military flying training. This simulation is being used by the MoD to evaluate the existing military flight training system (MFTS) and as the primary technical discriminator between industrial bids for the transition and future administration of the system. Simulation allows the military to create coherent policies for recruitment, manpower training and manpower planning. Optimization of recruitment, training and staff costs are possible while still achieving and maintaining the required manpower strength. Non-simulation tools (spreadsheets, databases, paper-based calculations of manpower requirements) cannot take account of the variable time delays inherent in a training and hierarchical manpower system.

UK Royal Air Force

The RAF’s Personnel Management Agency (PMA) simulates the effects of changes in its training pipelines on performance measures such as the rate of trained pilots ready for combat, the level of backlogs in the system, the time spent in training by cohorts of students and the sustainability of systemic solutions to managing the training pipeline.

Microsoft

Microsoft faced the challenge of communicating a new corporate strategy to 6500 sales and marketing managers at a global three-day conference. The Customer and Partner Satisfaction Simulation developed for Microsoft includes a detailed computer simulation that captures how each Microsoft employee impacts customer satisfaction. It included both Microsoft and industry data as well as video and text messages from simulated customers, colleagues, and industry figures. It demonstrated the impact of the strategy on major business metrics including customer satisfaction and stock price.

Ford Motor Company

Ford uses simulations of factory operations to evaluate and illustrate opportunities for improving supply-chain efficiency. Ford implemented recommendations suggested by the simulation and now forecasts its production needs more accurately, reduces problems such as last-minute changes, and is continuously shortening suppliers' production and delivery cycles. All these improvements led to $800,000 in savings at one plant in the first year. Ford plans to incorporate many of the changes throughout the company and expects to save more than $200 million in production costs over a ten-year period.

McDonalds

Managers at McDonalds typically grow up within the company and have a strong understanding of the operational side of the business, but weak intuition concerning strategic and long-term decision-making. McDonalds created a course for mid-level managers on strategic thinking and decision-making. The Strategic Decision Making Simulation played a central part of this 3-day course. Participants in the course formed four teams, each representing a competing restaurant chain. Over six simulated years, the teams made decisions on pricing, promotions, restaurant expansion and operations. The course instructors alternated simulation rounds with instructional activities concerning strategic planning, communication styles, systems thinking, and other business topics. The simulation provided a concrete, dynamic case study in which participants could test their ideas and see real-world dynamics of the business. Participants left the course with a set of new skills and deeper insight on strategic issues that they could apply back in the field. 100-200 managers attend this course each year.