Managing risk in a rapidly changing market can seem like a daunting challenge. But, if done correctly, the opportunity is the successful transition to a future of meeting consumers’ needs and expectations reliably and promptly.
Manufacturers’ production and distribution networks are changing. A structural shift from mass production to mass customisation, driven by increased consumer choices, rapid technological improvements and global competition are all contributing to this change.
Mass customisation means more bespoke products and services that inherently challenge the adaptability and responsiveness of manufacturers’ supply and production systems. The supply side of the equation must become even more responsive to a characteristically volatile demand. Solving the equation will be the secret to success.
Managing supply to demand is not new.
And, whilst we may view this challenge as Economics 101, the difficulty lies in meeting consumers’ needs and expectations on time and with a high level of certainty.
In parallel with a transition towards a technologically rich environment - characterised by greater automation of production processes reliant on robotics, computer based decision making and predicative analytics - manufacturers need to maintain a focus on cost reduction, quality control and meeting consumer expectations with increasing dependability. This dynamic will require substantial investment in order maximise the opportunity to successfully evolve from current practices to the high-tech manufacturing environment of the future.
Any transition that incurs investment will typically involve a degree of risk. The big question is, ‘how do you make this transition, and how do you undertake this investment in a risk free, or at least minimum risk way?’ Because the solution to managing this risk relies on sophisticated risk management techniques, the method has to be integral to the transformation process.
Manufacturers who are successfully responding to the dual challenges of meeting consumers’ needs, whilst achieving high reliability performance in a challenging, dynamic and competitive market, are doing so through the application of risk management mapping and profiling.
Manufacturing is largely a volume business. Increased production volumes drive market and price competitiveness. The pace of manufacturing, therefore, creates a constant tension between market demand and the economic volume needed to meet consumer appetite and affordability. The complexities compound exponentially for organisations with a global production footprint and a network of manufacturing sub suppliers as part of their production chain.
To help alleviate the market demand/economic volume tension, some sectors within the manufacturing industry have chosen to outsource particular components of their process. However, if not planned and managed in a risk assessed way, diversifying manufacturing processes through collaboration and outsourcing of the supply chain has potential for outcome failure.
The Boeing 787 Dreamliner is a case in point. Production of parts needed to construct the airliner occurred at multiple localities around the world, with centralisation of assembly taking place at the Boeing Factory in Everett, Washington, USA. Supply chain complexities and logistical hurdles resulted in significant delays in production and greatly delayed delivery to clients.
When considering the challenges faced in the manufacturing industry, cognisance of active risk management has received global acceptance.
Embedding active risk management into their existing business processes will set manufacturers on a path to thinking about risk in a new way. The outcome of this different thinking will be a sense of opportunity and achieving outcomes with greater confidence.
Risk Management, as a discipline, casts a wide spectrum; however, the manufacturing industry, and particularly process driven entities, can benefit from considering the multi-dimensional operational optimisation approach illustrated in figure 1.
Figure 1: Multi-dimensional operational optimisation
Operational optimisation, as shown in the centre of figure 1, purports the need for risk management at three distinct and equally important dimensions: Risk profiling, asymptomatic risk optimisation and risk trending analysis.
1. Risk profiling
This dimension enables manufacturers to monitor the receiving environment in which the manufacturing occurs. Risk profiling provides a framework of macro-environmental factors (political, economic, social, technological, environmental and legal) impacting the operating environment.
Risk mapping is largely an output of a risk analysis process. This could be at a qualitative and/or quantitative level across multiple risk categories: assessing the level of potential risk (uncertainty) of financial, brand and reputation, health and safety, as well as statutory and regulatory receptors. This phase provides a level of granularity in terms of understanding potential challenges needing proactive management to ensure operational optimisation.
2. Asymptomatic risk optimisation
Based on the philosophy ‘treatment is better than cure’, asymptomatic risk optimisation seeks to determine indicators of potential risk, dubbed ‘symptoms of risk’. They include, a process risk audit, coupled with management engagement around operational choices (e.g. technological options, resourcing and efficiency appetite). For example, stressed equipment that generates heat - such as worn bearings on conveyor systems or loss of energy from dated motors and pumps. The list is endless and specific to each manufacturer.
Once the symptoms are determined, treatment options are considered. Note, as treatment options range in effectiveness to the impact on performance ratio, a calculation is required to determine the return on investment ratio. This is a tricky assessment; risk is integral to all business operations and treatment options need to be practicable within the manufacturers risk appetite.
3. Risk trending analysis
Risk trending analysis is a forward thinking concept, since traditionally trending analysis implies tracking historical performance. That said, determining trends is the objective of this dimension. Two parameters steer the course for manufacturers, namely fully understanding and satisfying consumer expectations, whilst grappling with market demands.
Here the value of the GeoRisk, RiskMap and RiskLit come into play, as the context is largely defined through credible and robust risk management processes.
Decision making becomes simpler as understanding of the context grows; proactive management of operational regimes begins, equipping manufacturers to supply against predicted demands, within the desired expectations of the consumer.
Each dimension occurs in an unpredictable sequence. Thus, risk management should be undertaken simultaneously. This procedure will reduce the level of uncertainty in which manufacturers operate.
The inevitability of a technologically rich manufacturing industry brings with it a new set of risks manufacturers need to consider and manage to ensure operational optimisation. Such risks may include technology costs, maintenance, labour unrest and trend forecasting variances. A thorough application of risk management tools and techniques is essential to predict the risks inherent in this transition and to plan accordingly.
Risk management will provide a view on the level of uncertainty through probabilistic assessment techniques, coupled with softer risk management issues: geographical challenges and risk, and will, through risk profiling, inform sound decision making. At a state enterprise risk management round table in March 2005, when predicting future trends, GM stated the following, “Industry moves past lean and Just-In-Time manufacturing to risk-informed operations management” . This approach, GM submitted ensured the key attributes of: supply chain redesign to achieve resiliency and robustness; product design issues – modularity; dynamic pricing and revenue management to respond to risks.
At a micro level, asymptomatic risk optimisation will focus on the process(s) that ensures production attains and sustains high levels of reliability by voiding symptoms of risk before they manifest causing production destruction.
Improved risk management will provide the intelligence to help manufactures predict and plan rather than react. It will create the foundations for a smooth transition to a technologically and knowledge rich environment. And, it will help manufacturers create an effective balance between operational goals and delivering the quality of products/services and consumer services expected of their brands.
Presented at N.C. State Enterprise Risk Management Roundtable, "Managing manufacturing & supply chain risks in global automotive operations". March 18, 2005