Aug 16, 2021 | Lean, Management, Operations
Anyone who has read ‘The Goal’ by Eli Goldratt, the original brain behind the theory of constraints, will remember the story in the book about Herbie, the slowest walker in a scout group in a cross-country walk. Herbie was the bottleneck, in that he set the pace of the others, as the group did not want to leave Herbie behind in the woods.
One solution would have been to just get Herbie to walk faster, but that would have moved the ‘bottleneck’ position previously held by Herbie to the next slowest walker.
Whatever they did, the line of walking scouts would spread out, particularly going uphill, and then squeeze back in, going downhill. A walking accordion.
How do you prevent such a hard to manage outcome?
You get everybody to walk at the same cadence, with the same step length.
Standardisation of all aspects of the stride of each scout and the distance between each, would ensure that they stayed exactly together, in unison.
Armies call it ‘marching’.
I call it ‘Standardisation’ when applied to any context other than ‘walking’.
Marching enables groups of soldiers to arrive at a destination at the same time, in unison, that both gives the soldiers a sense of ‘belonging’ and looks intimidating to any opposition who might turn up to fight. Remember the opening scenes of the movie ‘Gladiator’? The Romans were in their ‘Centuria’ operating as one, but in coordination with the Centuria around them. The ‘barbarians’ who substantially outnumbered the Romans fought as individuals. You know who won. (I know it was a movie, but the lesson remains)
Standardisation to a cadence is the best way to finish the most work in any given time, as the variation and resulting shortages and backlogs are eliminated. ‘Flow’ through the system is optimised.
When you want to evaluate something new, you have a standardised system to test it on, and can therefore see the results of the change of one variable to the outcome. If favourable, you can then apply the single change to the entire system to improve it.
Going back to marching. The US army marching cadence is a standardised 30 inches for each step. Every soldier steps 30 inches every time. If the standard step was 31 inches, and the cadence of the march remained unchanged, it would represent a 3.3% increase in the distance marched in any given time.
Standardisation and continuous improvement, an essential element in optimising the performance of your business.
PS. 24 hours after publishing, I stumbled across this article by Brian Potter which goes into a heap of detail on exactly the topic of this post. For those who want a deep dive, I recommend it.
Aug 4, 2021 | Change, Management
Time is the most important, and only non-renewable resource we have.
We all have exactly the same amount every day, week, and month. It is how we use it that counts.
It seems common that almost none of us have enough of it, yet we all know we waste a lot.
If you are like me, you have tried all sorts of things, lists in many forms, blocking out time for specific tasks, all the way to leaving it to someone else to manage your calendar.
None have been wholly successful, which I put down to my own lack of discipline and routine.
However, there are several techniques to make it easier.
The ‘top 3’ technique.
I use this a lot in workshops, where the challenge is a lack of common focus amongst a group of executives. It works equally well on a personal level.
- List all the priorities on a whiteboard that those in the group are working on.
- Combine those that are common. This usually brings what can be a large number down to 15 or so.
- Weight them all, by putting them in order of importance, one to however many you have.
- Draw a line under number 3 and declare that these are the only three things we are working on, the rest are in a parking lot, to be brought out when one of the three top priorities is completed.
It works, mostly, and then usually only for a while so it gets repeated.
The 6 questions technique.
Six very simple questions, all of which require an answer.
- What will you stop doing?
- What will you start doing?
- What will you continue doing?
- What should you do more of?
- What should you do less of?
- What are you building?
That last question is the only strategic question, the other five are all tactical.
I would suggest you use Warren Buffett’s technique, which obviously works for him. He leaves a lot of time uncommitted to accommodate the opportunities that emerge, think creatively, and deal with the unexpected.
There are many other methods, find the one that works for you, and make it a habit.
You will be far more productive as a result.
Jul 28, 2021 | Analytics, Management
Many if not most marketers, approach metrics that seek to increase their accountability with about the same enthusiasm they would approach a snake of unknown species in their backyard.
Warily.
The default has become a range of numbers that might look useful, are ‘saleable’ in the corner office, but usually do little to hold marketers genuinely accountable for the outcomes of the decisions they make.
The most common I have seen are:
- Vanity metrics. Typified by ‘likes’ or number of ‘friends’ on Facebook.
- Measuring what is easy to measure instead of measuring what is important, the drivers of outcomes.
- Measuring activity rather than results. This is endemic in publicly funded organisations.
- Measuring for efficiency rather than effectiveness. You can be highly efficient at doing exactly the wrong thing.
- Concentrating on cost rather than the return that the investment generates. This measure, as does the following one, infests organisations of all types.
- Measuring budget compliance.
Charles Goodhart, a professor at the London School of economics proposed what has become known as Goodhart’s law: ‘When a measure becomes a target, it ceases to be a good measure’
The implication is that you need two opposing measures that drive the outcome you are looking for to use as KPI’s.
For example: We all know that the best lead is one we get from a satisfied customer, a referral. Therefore, it is easy to set as an objective the number of referrals given. Unfortunately, this is very easy to ‘game’.
Sales people are able to just extract any old name from customers, to reach the number. Therefore, it follows that the KPI should be referrals that are converted into a sale. Better, that ensures that the referrals given are genuine. However, it is also flawed, by the simple fact that a conversion can happen for a number of reasons, including a below cost deal.
Therefore, the related KPI should be around the margin, or perhaps customer cash flow, something that reflects the profitability of converted referrals. This will ensure that the referrals are in fact worth having.
Developing KPI’s that are held across functions will improve the flow of information and resulting functional performance.
I refer to these as Tandem and Opposing KPI’s. For example:
- Sales people responsible for revenue should also be responsible for margin, but not for setting the prices beyond a proscribed band. Those who set the prices should also have margin as a KPI.
- Operations people responsible for efficient manufacturing should also be responsible for inventory levels and stock turn. This should connect manufacturing to market demand, and ensure some level of collaboration with sales to ensure stock availability.
- Those responsible for management accounting reporting and implementation, should also be responsible for reducing operational transaction costs.
Marketing is often accused of using garbage maths, fancy but meaningless clichés, and often they do. For credibility this must change.
It is not only marketing that overuses garbage metrics. It is just that marketing is an easier target than the accountants and engineers who have some numerical street cred and get away with it more often.
Having a simple set of cross functional metrics that go to the drivers of performance at any level, that are openly displayed, will be a huge step towards performance improvement.
Header cartoon credit: xkcd. https://xkcd.com/2295/
Jul 14, 2021 | Analytics, Management
The ‘Standard Error’ is another of those confusing statistical terms marketers need to understand. It is often confused with, and is as misunderstood as ‘Standard Deviation’. While they are related, and the Standard Deviation calculation is used in the calculation of the Standard Error, they tell entirely different stories.
The standard error calculates how accurate the mean of any sample from a population is likely to be, compared to the true mean of the total population.
An increase in the standard error means that the means of varying samples of data are spread out, so it becomes more unlikely that any mean of a sample will be an accurate reflection of the true population mean. The higher the standard error, the more spread out will be the population around the mean. Conversely, a low standard error indicates a closely distributed data set, and so is more likely to be representative of the population.
To continue the example in the earlier post explaining Standard Deviation. If you were planning to improve Sydney’s terrible road congestion, it would be valuable to know how representative of the total commuting population of Sydney the mean of your trips from Artarmon to the CBD of 30 minutes was.
To do that, you would do a wider study of the whole population, and calculate the mean, and standard deviation. You would then apply the Standard Error formula to calculate the standard error of the Artarmon sample, compared to the mean of the whole Sydney population.
The standard error is the standard deviation divided by the square root of the sample size. It therefore tells you the accuracy of a sample mean by measuring its variability from the known mean of the total sample.
Header illustration courtesy Wikipedia.
PS. I guess the government could have done such a exercise in parking lots, swimming pools, women’s change rooms, and all the rest. Perhaps they do not understand real statistics when disconnected from political statistics?
Jul 12, 2021 | Analytics, Management, Marketing
Marketers often hear the term ‘Standard Deviation’ during research debriefs, and conversations with operational personnel managing quality. Many do not know what the term means, and in what context to use it.
Standard Deviation is a statistical term that measures the variation in a set of values from the mean, or average of that set of values. The greater the standard deviation, the greater will be the spread of the data from its mean. In effect, it gives you a level of confidence in the conclusions drawn from the data.
Those values can be anything, from the time it takes for you to travel to work each day, to the variation in the size or weight of a widget coming off a production line, or indeed, from any individual part of that production line.
Take your pre-covid commute as an example. You live in Artarmon, 10km’s from your Sydney CBD office. The drive can take anything from 15 minutes to 110 minutes. If you recorded the time taken for a period, say 3 months, assuming you worked every weekday, you would have 130 data points of the time it took to make the commute, to and from work. Assume you took an average of those times, and it was 30 minutes. The Standard Deviation calculation ‘translated’ means that in 68.2% of the commutes, your travel time would be within one standard deviation of the mean of 30 minutes, and 95.4% of the commutes would be within two standard deviations of the mean of 30 minutes.
Let us assume the distribution of the data points led to a calculation of one standard deviation being 7 minutes. In other words, 68.2% of the time you would complete the trip between 23 and 37 minutes. That calculation also results in 2 standard deviations being 17 minutes, meaning that 95.4% of the time you made the commute between 47 and 13 minutes.
Those ‘outliers’ falling outside two standard deviations will be unusual situations. You went into work at 2.00am for a conference call overseas, and you got to the office in 10 minutes, and one morning, there was a ‘prang’ on the bridge, and it took over 2 hours to make the journey. These would be the journeys that made up the very unusual data points in the set, out at 3 standard deviations, within which 99.7% of journeys fell, or further.
This might seem a bit quantitative for many marketers, but if you are to be taken seriously in the boardroom, you need to be able to speak ‘Data’ the language of the boardroom. The typical marketing type assurances based on opinion and theory must be at least partly replaced by the quantitative language of the boardroom.
For those looking for a bit more, there are plenty of resources on the web, and there is a SD formula in Excel which leads you through the steps to do the calculation. However, in principle, the calculation has a few steps:
- Calculate the square of the differences between all the data points, and the mean, then add them up.
- Divide that sum by the sample size minus1, which gives you the variance. The variance is a statistical picture of how spread out the data points in the set are.
- Calculate the square root of the variance, to give the Standard deviation.
As a marketer, you do not have to know the formula, but you absolutely must understand what the term ‘standard deviation’ means, and where it is best used. It might be useful to ‘fiddle’ with the formula in Excel.
Header graph from Wikipedia.
Jul 7, 2021 | Governance, Management
Small and medium businesses have many advantages over their larger rivals. They also have many disadvantages, which centre around the more limited resources they have to get the job done.
One of those disadvantages rarely spoken about, but sadly, present too often, is the lack of robust book-keeping procedures, which can and too often does, enable fraud.
This comes usually from the lack of internal controls, coupled with the ‘all hands in’ necessity of SME’s which means basic financial security measures are curtailed. For example, the recording of both debtors and creditors is in the hands of one person, or even simpler, there is little scrutiny on such items as credit card usage.
The propensity for fraud, and/or misleading financial reports and results can be looked at in a similar manner to fire.
For fire to occur, there needs to be 3 things in place. Fuel, oxygen, and heat. Take away any one of these 3 factors and fire cannot occur. If there is no fuel, it will not burn. Take away oxygen by covering the fire with water, or a fireproof sheet, and it will not burn, take away the heat source, and the fire cannot start.
It is the same in finance.
The 3 factors are opportunity, pressure, and rationalisation.
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- Pressure. For an individual to perpetrate a fraud, there must be some pressure for them to do so. Some situation in their lives that makes them take what they know is a risk creates the pressure to take that step. Debt, divorce, a burning desire to own something they cannot afford, and so on. Then there are a few who are just opportunistic, and when the opportunity arises, will leverage it.
- Rationalisation. The individual must be able to rationalise the fraud, stealing by another name, in some way. They need the money more than the company, nobody will notice a bit going missing every month, ‘I have been underpaid for the value I add’ and so on.
- Opportunity. There must also be the opportunity for the fraud to be perpetrated. The easiest way is to gain access to cash before it is counted, as in retail environments, but the lack of controls in a bookkeeping function or warehouse can have the same impact. I have seen payments clerks set up an account for a phony supplier, generate invoices from that phony, and pay them. I have also seen an order for 10 pallets have 11 pallets loaded onto a truck for delivery and the extra pallet not accounted for. This may not be financial fraud, it is stealing, and the effect is the same. Involving more than one person to perpetrate a fraud makes many types more possible, while at the same time, offering greater detection opportunity.
Remove any one of the 3, and fraud is far harder. Not impossible, but harder.
There are many simple things that management of any enterprise can do to minimise the occurrence of fraud in their business.
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- Separate the recording from the physical. The obvious example of this is the use of a till in retail that records the products and amounts bought, which then must be reconciled with the actuals in the cash drawer. This also records the products being sold which can be reconciled with stock records in a stocktake, further eliminating a source of opportunity.
- Separate the two sides of a transaction or create transactions as a data collection point. For example, the separation of the recording and payment of a debt should be separate to avoid the ‘phony’ customer situation. In a factory, you might institute a data collection point using bar coded pallet numbers on transfer from the factory production floor to inventory. This separates inventory from the waste stream, sometimes the source of an opportunity, as it was in the example noted above. This latter example also offers management some of the data necessary for improvement projects as an added benefit.
- Regular and close management of the debtors and creditors ledgers with the bank accounts. This will detect unauthorised payments made from the bank accounts.
- Restrict manual transactions, particularly where they involve cash.
- Control access to the books to ensure accountability of individuals for accuracy and completeness.
- Build in multi person authorisation into standard processes.
- Have clear transaction audit trails, that are monitored.
If some of these seem a bit ‘over the top’ for an SME, I understand. However, the volume of fraud that goes undetected and unreported is huge, and very damaging for an SME without the financial depth to easily navigate the losses.
Implementing some simple safeguards is just responsible business practice.
Get some help if you need it, and usually the return on a modest investment will be very quick.
