1.) "Organizations, like individuals, grow comfortable with the ways they have always looked at things and they are good at shaping the world to fit these ways. Mindsets get reinforced and worldviews become a dominant logic.....As long as the world is moving in (relatively) predictable directions, staying with the old cognitive framework is not such a bad thing. The challenge comes when the rules of the game change and fresh thinking isneeded." Quote taken from "Change is closer than it seems" by Andrew White and John Bessant in the Financial Times Series Mastering Uncertainty: Part 3:Don't get swept away by change March 31, 2006.
Strategic discussions often involve the most subjective inputs in the ERM process. How should the ERM process address this issue of entrenched "mindsets" so that they do not increase risk and reduce opportunity?
2.) "What makes liquidity so important is its binary quality: one moment it is there in abundance, the next it is gone....Liquidity comes in two closely connected forms: asset liquidity, or the ability to sell holdings easily at a decent price; and funding liquidity, or the capacity to raise finance and roll over old debts when needed, without facing punitive ‘haircuts' on collateral posted to back this borrowing." Quote from The gods strike back: A special report onfinancial risk in The Economist February 13, 2010.
Financial Risk models, such as VaR, set "expected" loss levels based on probability models of expected asset returns and correlation of returns among assets. But the tacit assumption is that liquidity exists so the asset can be sold. Discuss the implications of Liquidity Risk for such models.
3.) "Uncertainty in supply chains is often blamed on external events such as bad weather or machine breakdowns. Although these are common, they may not be the biggest contributor to supply chain uncertainty. Indeed, research shows that the most common causes are ‘institutionalized' decision-making policies and information systems....Uncertainty in supply chains is frequently generated by a phenomenon called ‘deterministic chaos', which refers to dynamics within supply chains that are determined by fixed rules but that generate random behavior. A characteristic of deterministic chaos is it sensitivity to initial conditions, which mean that tiny changes over time can become dramatically amplified. This is analogous to the famous ‘Butterfly Effect', whereby the flapping of a single butterfly's wings generates a tiny change in the state of the atmosphere. Over time, this becomes amplified into a major disturbance to weather systems, such as a tornado in another part of theworld.
In the context of the supply chain, something similar to the Butterfly Effect can be observed in the/our [sic] use of decision-making and information systems. Over time, small alterations to those systems can have a significant impact on the supply chain. In theory, these changes should be predictable, because chaos is generated by fixed rules that involve no element of chance. But in practice, the non-linear effects of many causes make the system less predictable. Decision-making and information systems are also extremely sensitive to initial conditions, so infinitesimal change to a variable can result in a completely different response.
This raises a fundamental issue about the impact of chaos on computer systems. An identical program run on two different makes of computer, or different standard software packages doing the same calculations can, under certain circumstances, produce significantly different results. Simple chaotic behaviour can even be found with commercially available spreadsheets.
Research into stock management decision-making undertaken by John Sterman at MIT has demonstrated that the more complex forms of deterministic chaos occur when managers are over-ambitious with setting low inventory levels. The research also found that, when such policies are applied, costs were 500 percent greater than optimum. This phenomenon can be witnessed in practical industrial environments, where driving inventory down to low levels can result in problems caused by products being out of stock, rapid and erratic reordering and poor customer service levels." Quote taken from "The ghost in the machine"by Richard Wilding in the Financial Times Series Mastering Uncertainty: Part 4: The search for common meaning April7, 2006.
How should an ERM process approach this issue of a "ghost in the machine"?