Risk Analysis Solutions

As the UK continues to suffer from unseasonal weather patterns, serious flooding is a very real possibility. This can have a severe impact on water assets and services.

Halcrow, a CH2M HILL company, has developed a programme to mitigate the consequences of severe flooding in the UK. It determines the risk faced by critical assets such as water treatment works and pumping stations and weighs it up against the cost of appropriate preventative measures. @RISK is used to quantify the uncertainties in this process.

Halcrow first identifies the likelihood that a site will be subject to fluvial flooding and quantifies the vulnerability and consequence of failure for each asset. Recommendations to improve flood resilience may include adaptive solutions, such as designing structures to reduce the consequences of flooding by facilitating recovery from it. Alternatively, resistance, which aims to prevent flooding in the first place, might be more appropriate for some sites.

For example, rectifying the consequences of a flooded water treatment plant can be very expensive. The physical damage to pumps and equipment needs to be repaired, and there are additional costs that may be incurred, such as bottled water supply while the plant is out of action, and customer compensation for lack of service. Working out the costs of these consequences will help to determine the right solution for the individual site. However, it is difficult to quantify the exact costs so @RISK is used to quantify the variations in the figures.

@RISK is also used to measure levels of uncertainty for other key aspects that have bearing on the eventual outcome. For example, there are uncertainties around the direct damage costs and the expense of responding to customer contacts associated with the incident. At the same time it is important to understand the level of uncertainty in the costs of intervention, such as building a floodwall.

Halcrow set out to understand what it was realistic to mitigate against and therefore what could be achieved in terms of the costs and benefits of improving the current levels of resilience. The nature of the task means that each stage of the calculation is subject to uncertainty, but @RISK enables it to measure each eventuality and make an informed decision on the best course of action.

» Case study: "Halcrow uses @RISK to determine level of flood resilience required for UK water assets"

» Related: How can the UK public services prepare for unpredictable, extreme weather?
 

Accenture recently released research illustrating that mining and metals companies could "significantly reduce the costs of large capital projects" by improving their risk analysis and management methods. With billions at stake, and delays and budget overruns the norm, the need for better systematic accounting for risk has never been greater. Accenture’s research was based on 31 interviews with mining and metals executives around the world."

In a recent issue of Supply Chain Digital magazine, Palisade's Randy Heffernan explored the relevancy of risk analysis solutions for supply chains. 

"Managers need to be able to answer questions like: 'What is the probability this critical part will arrive on time?' and 'What are the chances of failure at this point in the process?'" says Heffernan. "[Risk analysis techniques using Monte Carlo simulation] allow decision makers to perform trade-off analysis among expected costs, quality acceptance levels, and on-time delivery distributions. It also provides alternative tools to evaluate and improve supplier selection decisions in an uncertain supply chain environment."

Supply Chain Digital covers the global supply chain space, from how parts are sourced to how packages arrive on your doorstep. It is a leading source of logistics, procurement, warehousing and outsourcing news geared toward executives in the supply chain industry around the world.

» Read the complete article: "Risk Analysis Will Drive Better Decsions Across the Supply Chain"

New DecisionTools Suite version 6.0 includes a wide range of improvements, including powerful new integration of @RISK with Microsoft Project that allows you to perform risk analysis and Monte Carlo simulation on your Microsoft Project schedules – all from the @RISK for Excel platform! @RISK also adds simulation of time series models, easier-to-understand tornado charts to identify risk drivers, better graphing options, improved distribution fitting, and new distribution functions.

But there’s more to DecisionTools Suite 6.0 than just @RISK. PrecisionTree 6.0 adds powerful Bayesian revision and the ability to insert nodes anywhere in a tree. RISKOptimizer and Evolver 6.0 now include the OptQuest solving engine for even faster solutions on many types of models. RISKOptimizer, which has always shared functions with @RISK, is now even more tightly integrated with @RISK for seamless modeling. And StatTools and NeuralTools have added improvements to scatter plots and sensitivity analysis to the testing of neural nets.

» See What’s New in DecisionTools Suite 6.0

When you think of heating sources, what comes to mind? For most Americans, oil, electricity and gas are the obvious choices. What about wood pellets? Wood-burning heat sources often conjure up images seen on “Little House on the Prairie”. However, in Europe wood  pellets are in high demand as a home-heating option. Besides being more efficient and less taxing on the environment, European regulations encourage the use of carbon-neutral sources. This is great news for U.S. wood-pellet producers, who expect to see a sharp demand for their product over the next decade.

FutureMetrics is one of the leading domestic experts in the economics of the production and use of renewable bioenergy. They, along with their partner Innovative Natural Resource Solutions, formed a new company, FutureEnergy Partners, to focus on the economics and risk of wood pellet production. Using @RISK, they performed risk analysis simulations to address some very critical concerns regarding the bright future of wood-pellet production:

• How much wood is required to operate a wood-powered plant and produce the appropriate amount of wood pellets to keep up with demand?
• How do they hedge their prices against global wood prices in a fashion that will allow them to turn a profit?

In a very informative case study, FutureMetrics shared its use of Monte Carlo simulation to answer both of those questions and secure a bright (and warm) future for U.S. wood pellet producers. It will be interesting to see if the U.S. moves towards alternate heating sources, such as wood pellets. If so, we’re sure @RISK can offer the kind of clear risk analysis necessary to make it both possible and profitable.
 

» Case Study: Futuremetrics Uses @RISK to Hedge Wood Prices in Production of Burning Wood Pellets

There's an important event coming up in just a few short weeks--"Profit through Process," the IQPC Lean Six Sigma summit.  The summit is an almost week-long conference in Orlando, January 17 through January 20. IQPC has rounded up about 800 experts to deliver their knowledge, insights, and often inspiration to the folks who attend.   These presenters represent some high-profile companies like BP and PayPal, as well as leading consulting firms.

The sessions have been organized to satisfy the hankerings of everybody in the Six Sigma-process optimization crowd, from the chief quality officer to the Black Belt. And one thing I think will be really productive for the folks who get down to Orlando is the conference's emphasis on integrating a Lean Six Sigma program so that it becomes a living part of the organization.

Eight hundred is a lot of experts, who should have a lot of useful ideas about driving profit through process improvement.  And will be a lot of useful tools to check out.  Which brings me to my role at the summit--how can I sign off on thes blog without putting in a plug for Palisade?  I'll be there with our Monte Carlo software--booth #7--extolling the virtues of Monte Carlo simulation for Lean Six Sigma.  Monte Carlo simulation is a relatively recent addition to the Six Sigma toolkit, and while you may not think risk analysis is central to process optimization, it is really about getting a grip on uncertainty--and you can certainly relate to that.

Please know the IQPC is offering a "Free Hall Pass" for those interested in networking or exploring the latest Lean, Six Sigma & BPM solutions.

Remember, it's January, and you can come to Florida!  Here's the website--www.leansixsigmasummit.com/Event.aspx?id=341814.

I hope to see you there!

This is the conclusion of Dave Roy’s guest blog, we hope you have found them informative. Again, Dave comes to us from SSPI, Six Sigma Professionals, Inc., and taught Jack Welch and his entire staff their Six Sigma Green Belt training. Also, look for Dave’s free live webcast on August 19^th, Assessing your New Product, Process or Service Introduction Methodology: Is yours premier? Does it enable Six Sigma performance?

Oops! Didn’t see that coming! Part 4
 

As a continuation from the July blog, we are now concluding with the “Optimize” and “Validate” phases of the ICOV (Identify-Conceptualize-Optimize-Validate) framework of a rigorous new design process as explained in “Services Design for Six Sigma – A Roadmap for Excellence”.

These phases are important because it allows time and methodology to optimize the design, develop all of the detailed documentation, verify performance and capability under operating conditions and manage an orderly transition to the new state.

The Optimize phase consists of a single stage (Design Optimization) and associated Tollgate 5 to validate successful completion of the requirements. 

The Design Optimization stage involves completing all of the detailed design documentation, building Prototypes of the design, simulating/analyzing Process Capability, preparing all Control Plans and updating the Design and Process Scorecards.

Tollgate 5 Exit Criteria:

o    Agreement that functionality and performance meet the customers’ and business requirements under the intended operating conditions.

o    Approval to proceed with the Validate stage.

Formal tools which can be used in this phase are Design Scorecard, Process Management, Mistake Proofing, Simulation, Change Management, Control Plans, Reliability and Robustness.

The Validate phase consists of two stages (Verification and Launch Readiness) and associated Tollgates (6 and 7) to validate successful completion of the requirements. 

The Verification stage involves developing Pilot plans, Piloting the new design and process and analyzing and making adjustments to achieve the desired functionality and performance under operating conditions.

Tollgate 6 Exit Criteria:

o    Agreement that functionality and performance from the pilot meet the customers’ and business requirements under the intended operating conditions.

o    Approval to proceed with the Launch Readiness stage.

Formal tools which can be used in this phase are Design Scorecard, Process Management, Mistake Proofing, Change Management, Control Plans, Statistical Process Control (SPC), and Confidence Analysis.

The Launch Readiness stage involves developing Pilot plans, Piloting the new design and process and analyzing and making adjustments to achieve the desired functionality and performance under operating conditions.

Tollgate 7 Exit Criteria:

o    Agreement that transition plans and training plans have been developed and are executable.

o    Approval to proceed with the Production stage.

Formal tools which can be used in this phase are Transition Plans, Training Plans, Process management, Change Management and Control Plans.

Following the ICOV model we have now used a formal methodology that allows us to validate performance at progressive economical stages and have improved the ability to detect unknown risks thus avoiding the Oops! Didn’t see that coming!. It should be mentioned that the methodology should be flexible and scalable to adjust for level of invention and risk. A brand new invention (Research & Development) that has never been deployed in similar conditions is much different than implementing a known solution (Application Engineering) under new conditions.

 » Part 1
 » Part 2
 » Part 3
 

BIO:

David Roy is an integral part of the Six Sigma community. He taught GE’s Jack Welch and entire staff Six Sigma, as well as served as Senior Vice President of Textron Six Sigma. He is a Certified GE Master Black Belt, was instrumental in developing GE’s DMADV (DFSS) methodology, and has taught 3 waves of DFSS Black Belts. David holds an BS in Mechanical Engineering from The University of New Hampshire. He is also the co-author “Services Design for Six Sigma – A Roadmap for Excellence”