In the investigation of the synthetic credit portfolio scandal at J P Morgan last year, senior executives have been accused of omitting key data from reports to its US regulator as losses mounted up to $6.2 billion. Bruno Iksil, a trader known as the ‘London Whale’ for the vast size and complex series of bets on credit derivatives, emerged as the culprit. The trades ‘created a runaway train that barrelled through every risk barrier,’ said Carl Levin, head of the senate permanent subcommittee on investigations in his report. According to him, ‘values (on trading books) were manipulated to hide losses; risk limits were ignored; the public was misinformed and oversight was dodged.’ It is interesting that such massive ‘accidents’ (seemingly random events) with potential to derail the entire financial systems can occur repeatedly in our society. That is the characteristic of complex, nonlinear systems where despite numerous controls, rogue behaviour can occur from nowhere. Large firms, as they grow in size, become as much human, political, and social entities as economic ones. They have to deal with increased uncertainty in dynamic and ever-changing environments.

An understanding of behaviour of complex systems especially under stress can lead to better decision-making, prevention of catastrophes and diagnosis and prognosis of ailments. There is considerable evidence now that the progression of chronic diseases and deterioration of patient’s health may not necessarily be smooth but could be laced with several transition points ultimately leading to the tipping point.

Predicting the point of no return is possible if the throughput series data on the firms is robust-enough. For instance, in our research on industrial sickness based on BIFR data of 167 firms, we found that it took on an average about 5-7 years for a sick firm’s net worth to erode by 50 per cent, but only another 1-2 years for 100 per cent erosion. The evidence was overwhelming. One can say that the critical threshold or the tipping point for such firms is when the net worth erosion gets past 50 per cent mark.

In dynamic complex systems, the transitional change could be non-linear and therefore, abrupt (both positive and negative). It becomes imperative for managerial leadership of large firms to look for early-warning signals (EWS) on a regular basis and be wary of their firm’s tipping points. Borrowing analogy from the medical sciences, business firms also exist in three states, viz. normal state (stable and managed growth), pre-disease state (signs of deterioration of financial and market-related health and slowness of responses), and disease state (an almost irreversible state where the firm is unable to fulfill its basic mandate and statutory duties). During the pre-disease state, it is possible to reverse the critical slowing down, with appropriate interventions to prevent further qualitative downfall leading to the tipping point.

Many scholars have tried to identify the EWS for business firms. The indicators can be categorised broadly as financial, employee-and productivity-related, and market-related. Though financial numbers and ratios are most robust parameters of a firm’s health, yet these are usually the lag indicators. It is the information from the market that provides the earliest and most promising signals (the lead indicators).

In a world full of uncertainty, it is hard to predict transition points, given that in a complex system, little or no changes may be visible before the tipping point is reached (just as cancer is detected sometimes only at an advanced stage). Yet there are certain generic stress points in a wide range of industries that can be the starting point for making sense of EWS. For example, every industry has a few market-related critical success factors on which every player in that industry has to perform well in order to survive. (For a retailer, it could be supply-chain and inventory management, for fast-moving consumer goods it could be marketing and distribution, among others). Critical success factors should be linked to the risk assessment practices adopted by the firm. Based on the risk-profile and critical success factors, the firm can develop a series of key performance indicators (KPI). As the name suggests, the board identifies a few key lead indicators for monitoring on a regular and consistent basis. The German commercial code called the Handelsgesetzbuch (HGB) requires establishment of a suitable early warning system that recognises risk indicators, which can jeopardise continued existence of the firm. It demands that auditors must audit the early warning system in accordance with the code.

There are several KPIs depending on what one wants to measure such as for value-added towards shareholders, employees, customers, and society. In my experiences, at least two KPIs are absolutely crucial to ensure continued good health of the firm, viz. the economic value-added (that is premium earned over cost of capital including equity), and positive free cash-flows. These measures can be tracked on real-time basis. The financial crisis of 2009 demonstrated that in a globalised world, markets have become much more multi-layered and dynamic, and less predictable. The winning attributes in the long-term may not be the biggest or the fastest, but the most adaptable companies.

(The writer is a professor of strategy and corporate governance, IIM-Lucknow)