A marketer’s guide to Operational Continuous Improvement measures.

A marketer’s guide to Operational Continuous Improvement measures.

Jun 12, 2025 | Lean, Management, Operations

Many owners of small manufacturing businesses, up to about 30 employees in my experience, have only a vague grasp of the measures and mechanics of continuous improvement. Having a stable process, then experimenting to do the small things better, every time you do them. The impact compounds. Lean Manufacturing and Six Sigma offer practical tools to boost performance, reduce costs, and improve your ability to serve customers.

Below are 9 key measures for continuous improvement. Pick the few that are most relevant to you and focus on them.

Overall Equipment Effectiveness (OEE)

OEE shows how effectively your equipment runs by combining machine availability, performance, and quality into one simple metric.

Inefficient or underperforming machines will quickly create bottlenecks in your operation. The whole chain can only go as fast as the slowest link, so identifying those bottlenecks and earmarking them for attention will improve overall effectiveness.

In these days of cheap digital sensors and data collection tools it is becoming easier and cheaper to instal machine sensors, downtime logs, and quality checks to monitor uptime, output rates, and defects.

Cycle Time

Cycle time measures the time it takes to complete a process, from start to finish. Shorter cycles mean more output without extra costs.

The measure can be applied to an individual part of the chain, or the whole chain, using a tool as simple as a stopwatch, or as complex as a SCADA system.

This measure is not to be confused with Takt time, which is a measure of the rate of demand.

First Pass Yield (FPY)

‘Get it right first time’ is a cliché that refers to first pass yield. It tells you how many products come out within specifications the first time, helping cut down on rework, scrap, and wasted effort. The principle of the measure is simple, but the trap is in making it too easy. A wide spread of acceptable specifications is more easily met than a narrow one, and will distort the measure, possibly giving you a wrong picture of quality performance.

There is a myriad of ways to check quality ‘at source’ i.e.: from random checks to sophisticated visual and digital mechanisms.

Lead Time

Lead time normally measures how fast you fulfill orders. It can also be usefully applied to parts of the supply process, such as the time taken to respond to queries, provide details, quotes, and many other points of customer interaction. Faster lead times mean happier customers, referrals and repeat business, and better cash flow. In a world that is accelerating at unprecedented rates, being quicker to respond is a powerful competitive advantage.

The easiest way to track lead times is to start automatically time-stamping everything, and tracking through spreadsheets, your CRM, or even by hand.

Reversing the focus of lead time, and measuring your suppliers lead times, and DIFOT (explained below) is also a powerful way of managing improvement in your operations, and therefore ability to serve customers.

Inventory Turnover

In simple terms, Inventory Turnover is how many times your inventory is sold and replaced over a specific period. It is calculated using the average inventory value in a period and your Cost of Goods Sold. The simple formula is COGS divided by Average inventory.

Accountants see inventory as an asset, that is how it is treated in the balance sheet. However, as inventory is a measure of how much cash you have tied up, immobile, it is to my mind a liability beyond a delicate balancing point that is necessary to serve customers. Too much inventory ties up cash and risks obsolescence, too little causes delays. Balance is key.

There are many inventory systems, all do the same thing. Monitor stock levels, keep track of the value, and usually flag repurchase time based on usage and nominated procurement lead times when fed sales forecasts.

Inventory turnover is often expressed as ‘Days cover’ in fast moving environments.  The formula is the same, the period is days.

Scrap, Rework and Waste Rates

Waste eats into profit. You expend time and resources to add to the scrap pile. Anything that reduces waste, scrap and rework will boost efficiency and margins.

Scrap is when you simply send a completed or partially completed item to the bin. Rework is when you invest further time and effort to turn a unit that could be scrapped into a saleable unit, and waste is the material left at the bottom of the ingredient bag, the leftover material after the templates have been stamped out. Each is different, each warrants attention.

As with the other measures, there are many ways of tracking these three ‘nasties’. Your accountant should be able to give you the numbers based on what is used to produce the inventory, and the difference is the place to start looking for the scrap and waste. Rework usually requires added time and labour which can be tracked.

Customer Complaints and Returns

Often the best source of problem identification is what your customers are telling you. A returned product can be a source of intelligence that enables you to track and pinpoint problems to be resolved before they escalate.

Keep records of customer feedback, returns, and service calls.

Equally, customer satisfaction is a useful measure, but challenging to build reliable data. Many enterprises use the Net Promoter Score method, alternatively monitoring social media feeds may deliver insight. However, when customers pay you their hard-earned money, they expect to be satisfied, just delivering what is expected is hardly reason for a party

Safety Incident Rate

Ensuring as far as possible the safety of employees is not only a moral responsibility, it is now a legal responsibility that in some jurisdictions has had the onus of proof reversed.

Factories can be dangerous, and removing as many of the sources of danger as is humanly possible is essential. Tracking safety incidents is a measure of how successful that effort has been.

Delivered In Full On Time. (DIFOT)

DIFOT is an overarching measure that pulls all the above together. Failure in your operational processes will make delivering in full on time challenging, if not impossible. It is one operational measure that should be on every KPI menu. As noted above, it is a very useful measure of the performance of your suppliers.

Efficient does not always mean Optimal.

Efficient does not always mean Optimal.

Oct 21, 2024 | Lean, Management

 

 

Seeking highly efficient processes is the holy grail of most operational managers.

Is it the right goal?

‘Garbage in.. Garbage out’ still applies, even if the garbage gets a slick coat of paint on the way through.

The process as implemented might be efficient, optimised, but does it deliver the outcome in the most effective way?

A typical example is from a while ago when the NBN was (compulsorily) connected.

The technician turned up just within the time window, to do the connecting work, and did it quickly and it seemed, efficiently.

After about 45 minutes, he informed me it was all done, all I had to do from there was connect up the modems around the house.

When I expressed surprise, that until everything worked, the job was not complete, I was told: ‘Not my job, I have 7 connections today, and I am behind by almost an hour’.

Clearly there was an optimised process of installation by NBN subcontractors in place, the final few feet being the responsibility of the retailer. However, as far as I was concerned, I had paid the compulsory $172 for ‘connection’ and it was not complete until everything worked.

It may have been an efficient process from the perspective of the NBN, but from the perspective of someone who had paid for a service, it sucked.

The technician was prevailed upon to ensure that the job was complete, to my eyes. The problem for him was he failed to meet the stupid KPI imposed by someone seeking an efficient process, rather than one that optimised the outcome.

Header image is obviously courtesy of AI, and is therefore not optimised by a human.

 

 

 

The critical unasked question that can kill a ‘5-why’ analysis.

The critical unasked question that can kill a ‘5-why’ analysis.

Aug 26, 2024 | Lean, Operations

 

‘Five Why’s’ is a commonly used tool, widely seen as one that when used well gives you answers to challenging operational problems.

Mostly it will, but what happens when the answer lies hidden outside the consideration of the effort to identify the cause-and-effect chains that lead to the problematic outcomes.

To solve any challenging problem, there are 4 stages that are used:

    • Collection of data
    • Analysis, segmentation, and classification of the data
    • Generation of a theory that might explain the condition and
    • Experiments to identify the cause of the outcomes rather than just the observations of it.

What happens when the third stage fails to produce a theory that explains under experimentation the outcome?

Go back to the basics, by looking at the data more widely, as clearly something is missing. Often it pays to reverse the process and ask yourself ‘what could have caused this outcome’ starting at the problematic result.

Years ago, Dairy Farmers limited had a monopoly in retail UHT processed long-life custard.  It was a modest sized niche market that was quite profitable. There had been several attempts by competitors to grab a piece of the action, all of which had failed.  Suddenly we started having problems at seemingly random times. When opened the custard was the consistency of water. The costs of lost production were substantial, but the far greater costs were those of the product recall from retail shelves, and loss of consumer confidence.

The condition was caused by either the presence of an enzyme called amylase, or a failure of the CIP system. Amylase is a naturally occurring enzyme in starch, which had been eliminated by processing from the complex hydrocolloid (starch) ingredient we used in the custard. We had accepted the assurances of the supplier that the ingredient supplied was amylase free, as per our specifications. We assumed therefore that the problem lay with the processing plant. The plant was torn apart several times, cleaned meticulously, and on one occasion, underwent some expensive engineering changes.

All efforts failed to fix the problem.

A valuable question to ask in this circumstance is: ‘What would have to be true to…..’ In this case, the answer would have been: ‘there is no presence of amylase in the hydrocolloid ingredient’. This may have, much earlier than it did, spark the further  question: ‘Is a test with a sensitivity level of 1 part per million a reliable indication that there is no amylase?

When we finally asked this question of ourselves, the answer was clearly ‘No’. We set about refining the test our suppliers used to a sensitivity of 1 part per 10 million. This more sensitive test showed up in a random manner, the presence of amylase in the supplied ingredient.

5-Why is a great tool. However, like any tool, it must be used by an expert in order to deliver an optimum result.

Header is courtesy of a free AI image generator, depicting some tortured engineers doing a root cause analysis..

 

The 2 mutually reinforcing ingredients to success:

The 2 mutually reinforcing ingredients to success:

Sep 11, 2023 | Change, Leadership, Lean

 

 

If there is a magic ingredient to success, it is captured in two words: ‘Leverage’ and ‘Compounding’.

We all understand the concept of leverage, using a small amount of force to generate a larger outcome.

Compounding is a little more difficult to understand, although if you currently have a mortgage, you are suffering the compounding results of higher interest rates eating away at your growth in equity as you pay the monthly piper.

Question is, how do you find and build on them to generate a sustainable level of profitability?

Our commercial entities are built on the correct assumption that you need leverage to scale. As you build scale, it becomes necessary to add management layers to leverage the capabilities of those the next level down. That is why our organisation structures are always pictured as pyramids, because they are, for the leverage they generate.

Leverage leads to compounding, and compounding leads to greater leverage: a self-sustaining cycle, until the system becomes gummed up with friction.

Friction in management terms ends up being hidden in the layers of authority necessary to act. The transaction costs, which are almost always hidden from easy view, can be commercially fatal.

Leverage also delivers power to those in a position to exercise it, and as we know, power is a drug with many side effects, some of them not so good.

Technology has changed the ratios between leverage and compounding, but not the basic arithmetic. They remain mutually reinforcing, but their management has become significantly more complex.

 

 

 

The reliable way to forecast manufacturing costs.

The reliable way to forecast manufacturing costs.

Jun 30, 2023 | Change, Lean, Operations

 

 

Several years ago I became aware of ‘Wrights law‘.  In the 1930’s, Theordore Wright an aero engineer proposed that: ‘For every cumulative doubling of units produced, costs will fall by a constant percentage’. This insight came from observing the performance of his own factories building aircraft during the thirties and over the course of the war.

While I do not have the numbers, intuitively after 50 years of observation, it holds very true.

That truth seems to hold over any manufacturing I have seen and read about, unlike its much better known sibling Moore’s Law. Gordon Moore observed the increase in the number of transistors that can be stuffed onto a silicon chip in a given period of time, and predicted that a doubling of numbers would hold consistently over the long term.

Therein lies the significant difference that manufacturers have come to rely on.

Moore’s law refers to technology improvements over time.

Wright’s law refers to the manufacturing cost reductions that come with scale.

I would suggest that the cumulative impact of the combination has had a potent effect on manufacturing costs of everything from the manufacture of simple widgets to solar panels, to the cost of human genome mapping. Wrights Law applies as scale builds, and technology  provides a catalyst to a tipping point that radically alters the growth curve, after which the graph finds a new normal in the relationship between volume and cost.

Australia for lack of leadership, foresight and capital has shied away from the investment required to light that catalytic fire many times in the past.

A primary example is solar panels.  We have known for a hundred years that solar energy could be harnessed. As a kid I used to burn leaves, paper, ants, and occasionally myself, with a magnifying glass. However, it took researchers at the UNSW to invent PERC (Passivated Emitter and Real Cell) technology in 1983 to kick off Australia being the international leader in Solar cell technology. Funding and the foresight to commercialise could not be assembled here, so the technology was used to develop the manufacturing industry in China, where Wright’s law has facilitated the growth of a dominating share of the world market for wafers, cells, and completed solar modules.

Forecasting manufacturing costs is at the core of every successful manufacturer. While in the early stages of commercialisation there will be a host of variables you need to be able to model, understanding the relationship between your cost base and scale will remove a significant weight from your shoulders when planning capital requirements.

Australia again finds itself on the cusp of being an international leader in Quantum computing, biotechnology, Hydrogen sourced energy, and rare earth extraction and value addition. Let’s not allow ourselves to be distracted this time, we may not get another chance.

Successful economies all have one thing in common: they manufacture stuff others want to buy. Australia’s history is littered with great ideas, and technical innovations that are commercialised elsewhere for lack of foresight, leadership and capital. We would be desperately stupid to let it happen again!

 

The simple solution to supply chain disruption. 

The simple solution to supply chain disruption. 

Apr 27, 2023 | Change, Governance, Lean

While there is no silver bullet, there is a lot of tactical advice around that will increase the dependability and resilience of your supply chains.

Shortening lead times, removing steps in the chain, paying a premium for service to specification, creative logistic management, making information transparent, and many others.

All will deliver some benefit, and together can make a dramatic difference, but miss the essential nature of significantly improving supply chain performance.

When you ‘flip’ the chain, changing the drivers of the chain from supply to demand, the game changes.

Developing a clear view of demand, and responding only to the signals of demand, rather than the often functional signals coming from within the vertical management hierarchies of supply chain participants, alters the nature of the challenges being faced.

It becomes a demand chain, rather than a supply chain, or even a value chain.

In lean parlance, there is the concept of ‘Takt time’. This is a measure of the ‘pull’ put on a supply organisation by the demand from customers. It is the production time required to meet customer demand.

The so called ‘bullwhip effect’, the magnification of fluctuations in orders back through the supply chain will be at least mitigated by application of a metric that reflects real demand from the market.

Remember the panic buying of toilet paper, amongst other things, at the beginning of the pandemic? The underlying demand had not changed, we still all went to the loo at about the same rate. However, the sudden shortage on supermarket shelves created by panic buying resulted in supermarkets increasing their orders on suppliers, who in turn increased orders on their suppliers. At each point in the supply chain because of the uncertainty, everybody was increasing their orders, building inventory, magnifying the boom/bust cycle of supply, creating a ‘bullwhip’ effect. This is where the trajectory at the tip of the whip is progressively magnified by movement back through the length of the whip. Swung hard enough, it will ‘crack’ just like your supply chain.

The challenge is to match the whole supply chain to the real level of demand coming from the marketplace, demand uninfluenced by short term hiccups in the chain. If there is a silver bullet, that is it.