Why are public bureaucracies crap at innovation?

Why are public bureaucracies crap at innovation?

Jun 20, 2025 | Change, Governance, Innovation

 

 

Australia’s governments over time have, rightly, believed that the commercialisation of innovation is the key to long term prosperity.

As a result, governments of all persuasions and at all levels dole out billions each year in all sorts of grants, subsidies, and parallel programs.

Then, on a regular basis we have enquiries by well meaning and usually highly qualified people that come up with similar conclusions that the previous few and often very expensive enquiries have delivered: we are crap at it.

In successive weeks, the PM and Treasurer presented their view of the challenges facing us at the National  Press Club. Both were very impressive performances, and in particular the treasurer hooked his agenda firmly onto the ‘Productivity’ challenge.

The Treasurer outlined the principles of his agenda. However, he did not get into the weeds of the sources of the failure to date that see us struggling with productivity in the economy, the problem to be solved. He did however acknowledge that hard to measure services are increasingly dominating, and we are all getting older, making the productivity challenge that much greater.

Sensibly after repeating the same mistake numerous times, and ending up where we are now, we should be asking ourselves ‘Why’.

My take on ‘Why’.

Bureaucracies have two conflicting, irreconcilable imperatives:

  • On the one hand, they want to be fair and treat everyone the same. This makes commercial in confidence often challenging. (perhaps I overemphasise this as a result of a very nasty incident in my commercial past that will never be forgotten)
  • On the other hand, they want to exercise discretion and take account of individual circumstances and technical advances made by program participants engaged in the various programs.

There’s no way to easily optimise these conflicting objectives at the same time.

On top of those two drivers of bureaucratic fossilisation, you have two further impediments in the Australian context:

  • The impact of personal ambition, turf protection, and management of public sector KPI’s that have nothing to do with outputs, but everything to do with inputs that hobbles public sector engagement.
  • Our federated system drives fragmentation.

Published today is an excellent analysis of the way forward by John Howard (not that one) from the Action Institute that I hope is widely read and deeply considered by those who will be involved in the treasurers  productivity roundtable in August.

 

 

 

 

How to Lose from a Winning Position

How to Lose from a Winning Position

Jun 17, 2025 | Change, Leadership

 

 

“They snatched defeat from the jaws of victory.”

That phrase echoes around footy grounds when a team, cruising to a win, suddenly collapses. The hunger fades. The cohesion cracks. The urgency evaporates.

Winners who stay winners do so because they never switch off. They stomp on a throat when they have the chance. And when they’re behind, they still believe they can come back.

Sporting analogies make great business metaphors. They’re colourful, visceral, and most of all, familiar.

Skype is a prime example of dropping the ball over the line.

Microsoft has been a cash machine for decades. Dominant, deep-pocketed, and ruthless when it suits. In short, they know how to win. But last month, they quietly walked off the field and took their former champion with them.

Skype was officially euthanised on May 5, 2025.

The original disruptor. The upstart that reinvented digital voice communication. The king of the mountain. Gone.

Skype began in 2003, the brainchild of two Estonians who wanted to reduce the cost of voice calls by using peer-to-peer protocols. The product exploded. eBay snapped it up in 2005 for $2.6 billion. Then in 2011, Microsoft bought it for $8.5 billion. It should have been a match made in heaven.

But inexplicably to me at  the time, Microsoft launched Teams in 2017, and from then on, Skype looked like yesterday’s hero. Despite a global user base, a household brand, and a treasure trove of usage data, Skype was left to wither.

Why? Only insiders can say for sure, but from the outside, it looks like the classic case of a team where the halfback and five-eighth couldn’t agree on the game plan. Maybe one group wanted to modernise Skype. Another pushed all-in on Teams. The result? Strategic paralysis.

Then came COVID, and video conferencing exploded. Zoom turned from a quirky tool into a verb,  others rushed to grab a piece of the expanding pie, and Skype appeared to be disinterested in even playing.

Microsoft had every advantage: distribution, brand, cash, data, development talent and loyal users by the millions, but they didn’t press the advantage. They coasted, and the game moved on.

So the final whistle has blown. Skype, once the dominant player, was taken off the field not by a better team, but by its own coach.

Small business owners: don’t assume past success guarantees future wins. Stay hungry. Stay alert. Don’t let a lazy midfield cost you the match.

 

 

 

 

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.

The ‘yesterday’ metric used by all mass market retailers

The ‘yesterday’ metric used by all mass market retailers

Jun 4, 2025 | Category, Customers, Demand chains, Marketing, retail

 

 

Mass market retailers all use the same, or very similar metric to measure store performance: Dollars revenue and/or margin per square foot, or linear shelf metre. In addition, they track the size and content of the customer ‘basket’ to optimise product range against those key performance measures.

This leads to a mindset of short term profit maximisation in the buying office, at the expense of everything else. Only senior levels talk about strategy, and then in most cases, they fail to grasp the qualitative reality of ‘strategy’ and fall back on the numbers.

Shoppers do  not care about your margins/sq metre, irrespective of how you generate it (price, stock turn, or supplier ‘shelf rentals’) they care about range convenience, on shelf availability, and of course, price.

But price is only one of the considerations, an important one, but only one.

Ignoring the others is asking for trouble in the medium term

Trouble is what the Australian gorillas now have.

Their domestic supplier base has been brutalised, and the leverage they can exert on international suppliers is way more limited, simply because they do not have the scale to apply the pressure. Now in the absence of a high $A, they are suffering, and that suffering is unlikely to ease any time soon as the economy is likely to flatten in the wake of the ‘stupidity blanket’ being thrown over world trade by the US administration.

In addition, they now have become populist targets for a body politic that has no idea of the economics and dynamics of the ‘paddock to plate’ supply chain.

The marketing default has become loyalty cards, an added incentive to shop at the same chain, as they will give you something in return. Trouble is you cannot buy loyalty, you can only earn it. How many do you know with a wallet stuffed with ‘loyalty cards’ who are not in the slightest ‘Loyal’?

 

 

Analysis, insight, and reporting are not the same thing

Analysis, insight, and reporting are not the same thing

Jun 2, 2025 | AI, Communication, Governance

 

 

Analysis implies the intelligent interrogation of data, the use of differing ‘frames’ through which to see the data, and to enable those non obvious connections to be made.

First you need ‘clean’ data, without which, nothing that follows will be worth much.

Thoughtful, critical analysis of data leads to insight, from which comes that elusive lightbulb moment.

Reporting is the opposite, it simply requires the cleaning, summarising and posting of the data without the critical thought from which real insight evolves.

No lightbulb.

AI is good at that, while not being good at generating insight.

Being data rich but insight poor is now a very common problem.

AI will not solve it for you, people are needed. Not just any people, seat warmers, but the right people with the curiosity and ‘why not’ attitude of youth, combined with the wisdom of experience and domain knowledge.

Unfortunately, these people do not grow on trees, ready for the picking. You have to grow and nurture them yourself, while recognising that many will move on at some point. The old adage of a rising tide lifts all boats is nowhere more relevant.