A marketers explanation of DIFOT, and its difficult sibling.

A marketers explanation of DIFOT, and its difficult sibling.

 

When you want to improve something, find a metric that drives the performance you want.

Pretty obvious, as most of us subscribe to the cliché that you get what you measure, while remembering Einstein’s observation that not all that matters can be measured.

Ultimately, what the customer thinks is crucial to success. Therefore, measuring the performance in meeting the customers’ expectations is always a good place to start measuring your performance.

Amongst my favoured measures is DIFOT.

Delivered In Full On Time.

That means not only the full order delivered on the day it is originally promised, with no errors of any sort, from quality of the product to the delivery time and accuracy of the ‘paperwork’.

DIFOT is a challenging measure, as it requires the collaboration and coordination of all the functional and operational tasks required to deliver in full on time.

As you fail to reach 100% DIFOT, as most do most of the time, at least at first, the failures are used as a source of improvement initiatives.

There is very little more important to the receipt of that next order than your performance on the previous ones. Never forget that, and measure DIFOT.

Hand in hand with DIFOT, you should also measure inventory cover.

The sibling.

You can improve DIFOT by simply increasing inventory when selling a physical product. Demand is inherently difficult to forecast, as it is the future, and entirely out of your hands. The challenge is to prevent your warehouses multiplying, and clogging the operational systems. The ideal situation is ‘make to order’, the ultimate shortening of the order to delivery cycle time.

The most common and very useful measure of inventory is ‘Days cover’. How many days of normal, average, forecast sales, whichever you prefer in your circumstances, do you have on hand to meet demand? This measure is extremely useful on a ‘by product’ basis, but when applied as an average across multiple lines with differing demand levels, can become a dangerous ‘comforter’.

Counter intuitively, the products that cause the most problems are the smaller volume ones, and new products. In both cases, demand is harder to forecast. The swings from out of stock to excess inventory can be erratic, particularly when a production line is geared to the larger volume runs of an established product as a driver of operational efficiency.

To achieve a 100% DIFOT while controlling physical inventory over an extended period is the most difficult operational challenge I have come across. As a result, it is amongst the most valuable to keep ‘front and centre’. The twin measures of DIFOT and ‘Days Cover’ are a vital element in addressing that ultimate challenge of customer service.

 

 

5 essential steps for an SME to prepare to go digital.

5 essential steps for an SME to prepare to go digital.

 

 

Almost every SME I visit or work with needs to one degree or another to be moving down the path towards ‘digitisation’.

For some, this means considering how the sudden appearance of LLM trained AI will impact on their competitive position, for others, it is still how to write a simple excel macro, and move bookkeeping from Mavis in the corner to a cloud package.

Just what does ‘digitisation’ mean?

For most of my clients it means automating some or all of the existing processes driven by bits of unconnected software and spreadsheets, liberally connected by people handing things over.

It is usually a real mess, and the evidence of incomplete solutions, misinformation, and shattered hopes lie everywhere.

The world is digitising at an accelerating rate, so keeping up is not only a competitive imperative, it is a strategic challenge. To survive you must evolve at least the same rate, just to keep up.

On of my former clients is a printing business, an SME with deep capabilities in all things ‘printing’ that enabled the company to be very successful, in the past. Their capabilities are terrific, highly competitive, if we were still in 1999.

If I use them as a metaphor for most I work with, there is a consistent pattern.

They do not see digitisation as an investment in the future, rather it is seen as an expense. This means that the challenges are not considered to be strategic. There is no consideration of the application of digital to their product offerings, beyond the digital printing machines, services beyond those that made them successful 20 years ago, and their business models, beyond what is demanded by the two biggest customers, who between them deliver well over 35% of revenue.

They have not considered digitisation of operational processes, beyond a 20 year old ERP system, which has not been updated in any meaningful way for a decade, and they still only use a portion of the capability. The reason for this is simply a lack of internal capability and awareness, and the lack of cash to invest for the long term.

They have not modified their organisational and operational culture. No digitisation effort can succeed without the support of an operating culture that encourages ongoing change. Organisational processes can be modified by decree, but they will  not stick. It takes everyone in the boat to be pulling in the same direction, in unison, to make the forward progress proposed by the digitisation nirvana. This takes leadership, and a willingness to be both vulnerable internally, and a strong ability to absorb the stuff from outside. You need to ‘get out of the building’ not to smell the roses, but to see the lie of the land, and understand where the opportunities and challenges are hiding.

The recognition of the critical necessity of change is where you get given one point out of a possible 10. The other 9 are reserved for taking action. A daunting prospect for most.

Following are the 5 steps necessary to become ‘match fit’.

  • Map the existing operational processes so you know what you are changing. The starting point!
  • Map and change the mindset of the people, so everyone understands the extent of the challenge to the business, and to them personally. This will prove very tough for some, so expect push-back.
  • Take small and incremental steps along a path that all understand leads to a digital future, which means that a lot of collaborative planning has been done. Look for some low hanging fruit where early wins are likely.
  • Ensure that there are the necessary opportunities for all stakeholders, but particularly employees to grow and change with you. Those that choose not to, also choose to work elsewhere. There are no free rides.
  • Ensure the resources of time and money are allocated uncompromisingly to the long-term outcomes. It is just too easy to put aside something that is important but not urgent for something that may seem to be urgent, but is not important to the transformational effort.

Most need outside help to get this done. Usually that help in the early stages is not found amongst software vendors who have a dog in the fight. It is amongst those who have ‘been there, done that’. It will also be a resource hungry beast, but assuming you feed it, and you have the right mix of project management and technical capabilities, the investment will generate returns quickly, just not tomorrow.

Header cartoon credit: Tom Gauld

 

The good and bad of AI impact on SME’s

The good and bad of AI impact on SME’s

 

 

 

Anyone who reads my stuff on any sort of regular basis will know I have been deeply engaged with the potential impact of AI on all of us, since I stumbled across ChatGPT in early December last year. Of particular interest is the apparent potential for efficiency gains, particularly amongst the SME manufacturers I serve.

On one hand, I have been excited by the potential of AI to generate efficiency and expand the operational scale of SME’s. On the other, scared shitless at the potential for bad actors to sneak into our collective pockets and steal everything.

I need to write to think.

It forces me to sort out the stuff swimming around between my ears, as when I can articulate it sufficiently to write about it in some coherent manner, it leads to some level of understanding.

So, here is my list of the good stuff, followed by the bad, as it relates to the core of my business: strategy and marketing, starting with SME’s and the written word.

The good things AI can do for you.

  • Summarising large blocks of copy, even when it seems very messy.
  • Brainstorming; ideas, subject lines, complementary ideas, headlines.
  • Editing and grammar. (I have been using the editing and ‘speak’ functionality of word for years, it is essential to me, and is AI that we now just treat as part of the furniture)
  • Assembling descriptions and fact sheets
  • Looking for logical holes in an argument
  • Repurposing copy from one platform to another
  • Research
  • Outline and first draft.
  • Translation and transcription

The stuff AI is no good at doing.

  • Humour
  • Reflecting current news and events
  • Factual reliability. (Sometimes, it just makes stuff up)
  • Finding a good metaphor
  • Being creative. The great irony with creativity is that AI opens a whole new set of what is possible with visual tools, which can then combine with verbal cloning tools to completely alter apparent reality.
  • Looking ahead
  • Breaking complexity down to ‘first principles’
  • Pouring another glass when faced by a blank page and a deadline.

Then there is all the other stuff AI will do, and evolve to do in the very near future, that is not writing. Graphic design, integrating currently separate digital systems (API’s on powerful steroids) identifying trends and holes in huge masses of data. The impact on medical technology is already profound. When the human genome was first successfully mapped in 2000, the cost of that first success was in the tens of billions of dollars. Now you can send away a sample and have it returned with your genome map for a few dollars overnight.

The key it seems, is to be very good at explaining to the tool what it is you want, in the detail a 5-year-old will understand. As the header cartoon illustrates, being human while driving this stuff will rapidly become the differentiator.

Header credit: GapingVoid.com.

 

 

The reliable way to forecast manufacturing costs.

The reliable way to forecast manufacturing costs.

 

 

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!

 

Where can a manufacturing business get money for nothing?

Where can a manufacturing business get money for nothing?

 

There is a simple answer, but the money is just a bit harder to find.

It is tied up in your current operations, consumed by all manner of things that do not add value to a customer.

Machine down time, rework, waste, on line inventory, double handling, and a host of other things that get in the way of a steady, predictable and continuous flow through a factory.

Progress to completion through a production process can only go as fast as the slowest point in the process. Working around these choke points entails either building WIP inventory, or slowing the faster parts down to the speed of the slowest part of the process. There is no third internal option, but ‘outsourcing’ the slow bits is sometimes a productive choice.

Progressive removal of any impediment to a predictable even ‘flow’ and you will save money. However, even more importantly, you will free up capacity that will give you the opportunity to sell more from the same fixed cost base.

That is where the gold hides: Money for nothing.

Do you want it?

 

5 measures of your supply chain resilience

5 measures of your supply chain resilience

 

 

Our supply chains are suddenly under great scrutiny given the frailties surfaced by Covid. Calls for a greater proportion of domestic procurement are now more common than ever, but is domestic availability the only answer?

Most supply chains are actually run by procurement and logistics people. While there is senior management oversight, the actual purchase choices are routinely made in lower levels of most organisations. To affect change, this is where we need to start, in the bowels of the organisation.

The KPIs of procurement personnel are generally around invoice cost, as it is easy to track. In future, the decision should be more about security of supply, and total procurement cost, which are much harder to measure, and availability which is relatively easy to measure, but in my experience is often ignored.

The huge caveat of course is that the CEO must give ‘permission’ for the procurement people to go off the reservation, and make the necessary changes, and risk buying other than from ‘IBM’.

We also need deep supply chain mapping that captures the dynamics of the chain, and all the transaction costs that apply, as well as the visible financial costs.

The KPI’s of procurement must change if we are to build the resilience of our supply chains.

  • Collaborative DIFOT analyses through the chain
  • Switch KPI focus from cost savings, usually measured against the invoice cost, to give greater weight to availability.
  • Tracking of the drivers of cost, quality and delivery throughout the supply chain.
  • Quantifying transaction and opportunity costs, (particularly of management time) at all points through the chain.
  • Measures of resilience such as alternative, qualified, and immediately capable suppliers, utilising differing logistics

Together these measures will give you a measure of the resilience of your supply chain, or its ability to recover competitive performance after a failure. The greater the number of nodes in a chain, the greater the risks, which become amplified as you move further way from direct control.

Local suppliers will have to be prepared for the scrutiny of their sourcing. Company A, procuring from Company B, where there are sub-assemblies necessary will want to stress check the suppliers to company B as part of their procurement processes. This will take supply  chain transparency to a whole new level. To this point the concerns have been mostly about cost and the time in the chain.  In future, it will go much deeper, digging into a range of items that deliver resilience and reliable quality.

The speed of recovery of  your supply chain after the inevitable disruption will be key to competitive  performance.