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By Citizen Reporter

Journalist


Business rescue statistics must be read in context

There is much more to the numbers.


Although official statistics suggest that only 9.4% of all business rescue (BR) cases are successful, this statistic must be seen in context of a complicated industry. It is however a false perception and not an accurate indicator of the reality.

According to the 2015 Business Status Quo Report, issued by the Companies and Intellectual Properties Commission (CIPC), the number of successes appears to be only 132, or 9.4% of a total of 1 398 cases.

There are however a number of limitations to this figure:

  • The term ‘success’ has yet to be formally defined;
  • Substantial implementation notices (the 132 number used above) are not complete or not submitted to CIPC;
  • The term ‘substantial implementation’ is a subjective measure and is unique to each business rescue;
  • Any change in the company’s Public Interest (PI) score is not reflected in the figure. (More about this score later.);
  • The eligibility of companies entering BR is not considered.

So how does one interpret these numbers as they do not tell the full story?

Business rescue is an environment intended to provide the “breathing space” required for a company that is experiencing financial difficulties and its rescue practitioner to develop and implement a business rescue plan.

First prize is to reposition the company by restructuring its affairs, business, property, debt, assets and equity so that it can once again trade in a normal and solvent manner. If this is not possible, the second prize is to deliver a result that produces a better return for the company’s creditors or shareholders than would result from an immediate liquidation of the company.

So how does one interpret success? The statistics that are available coldly look at headline numbers – the number of rescues – but do not take cognisance of the real underlying success factors. Much has been written about an apparent lack of success in business rescue – but the numbers are flawed and without context.

For example, we have seen abuses of the business rescue process for ulterior motives. These cases should never have entered into the realms of business rescue, but sadly they did (they should have gone into liquidation from the outset) and the result is that they skew the statistics against genuine business rescue initiatives.

The definition of success also carries a significant degree of ambiguity. A typical example would be when, as part of a (successful) business rescue plan, a company sells its assets as a going concern, and consequently liquidates the empty shell that is left behind. This is not recorded as a success by the regulator despite the fact that the business continues and by any other measure would be a success. There is no data available to demonstrate how often this happens, but this is a significantly measurable number of cases.

Look at the impact of business rescue on employees. Logically the preservation of jobs is a key driver for the creation of the business rescue regime. Three of us, working as senior business rescue practitioners, have compared notes and adding the outcomes from all our cases combined we calculate that more than 10 000 jobs have been saved. This is spread across 19 business rescue cases or groupings (some containing multiple legal entities). This is not an insignificant number.  If we were able to aggregate the total number of jobs saved across all South Africa’s business rescue cases to date, what would the number look like then?

In the current statistical regime, no cognisance is given to employees or to scale – an entity with one employee is accorded the same weighting as one with a thousand workers. For example, if 9 out of 10 cases fail and end up in liquidation –the reported success rate is 10%. But if the 9 failed cases collectively employed 200 people and the 1 successful case employed 1 500 people – measured on the basis of jobs saved the success rate of business rescue proceedings would leap to 88%.

This brings me to the importance of the Public Interest score – or “PI score”. In broad terms, a PI score in the Companies Act is calculated for a company by adding the following together:

  • the number of employees;
  • every R1 million of third party liabilities;
  • every R1 million of annual turnover; and
  • the number of shareholders.

A PI score of 500 or more is classified as a “large company”, 100 to 499 a “medium company” and below 100 a “small company”.  This has various applications in our Companies Act, including the required qualifications for the business rescue practitioner permitted to oversee business rescue proceedings at each level.

So let’s try address the business rescue statistics again by way of a hypothetical example, but this time using PI score to provide weighting:

The business rescue proceedings of Company “A”, a small company, fail and it ends up in liquidation. The business rescue proceedings of Company “B”, a large company, succeed and it continues in existence in some form – perhaps as a new entity. After the rescue, “B” has less debt and has lost employees, but it is still “alive” and trading. Logically “B’s” PI score will have reduced somewhat post the business rescue proceedings:

Company A:

PI at the commencement of BR proceedings = 50

PI at the termination of BR proceedings (liquidation) = 0

Company B:

PI at the commencement of BR proceedings = 1 500

PI at the termination of BR proceedings = 1 100

Thus the combined PI of A+B at the commencement of BR proceedings = 1 550; and at the termination of BR proceedings = 1 100

Success rate calculation: 1100/1550 = 71%

So perhaps in its most concise form, the measure of success of business rescue, and the mission of business rescue practitioners, should be redefined to be the saving as many PI points as possible. The more points saved, surely the greater the benefit that is delivered to all stakeholders – and the economy.

Peter van den Steen is Director: Metis Strategic Advisors (Pty) Ltd

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