Which 5 capabilities enable a leader to successfully scale

Which 5 capabilities enable a leader to successfully scale

Nov 23, 2018 | Change, Leadership

Virtually every business I come across wants to grow.

A few I come across want to, and are able to scale.

Scaling is different from just growing, it requires much more than being better at what you currently do. It requires significant change, invites risk, and for many is very unsettling personally.

The few that have scaled successfully all have in place a leadership that seems to have a few common characteristics, always in an individual, who is able to shape the organisation in ways that reflect the hunger to be different in ways that adds serious value to customers, and to scale as a result.

They create a vision that excites and engages those around them.

They are able to translate that vision into a clear strategy that provides a transparent framework for decision making, ensuring what not to do is as important as what to do.

They build the capabilities of those around them to enable the execution of the strategy.

They focus relentlessly on one thing at a time, and measure results that connect the outcomes to the strategy, daily, weekly, quarterly, bi-annually, and longer term.

They are good people. This seems counter to the public persona of the driving successful business person who scales a business successfully, but most I have seen who are the genuine leaders of a successful scaling, are also successful people in other ways.

When you want to see if your business has what it takes, give me a call.

Photo credit: Roberto Robitz via Flikr

 

 

 

Is AI going to take our jobs?

Is AI going to take our jobs?

Nov 21, 2018 | Change, Management

Some of them yes.

Those repetitive jobs where we do the same thing over and over, will be gone.

Let’s be clear about AI. It is artificial, it is not intelligent.

AI is very good at some things  we humans are bad at, but it is no good at what made we humans so successful.  The imagination, and emotion, the capacity to empathise,  and understand complexity we are born with is not artificial, and cannot be replicated by machines, at least not in the foreseeable future.

Machines can do things  faster and more reliably than us, and they do not go on smoko, no holidays, hangovers or emotional attachments to fellow workers.

Machines are fast and reliable, and fast and reliable is a huge benefit.

Machines are also very accurate, tell them what to do, they do it. Again, something we humans are not so good at, we tend to vary things around, sometimes just to relieve the boredom.

Machines do the routine, mind numbing tasks that we put aside, or do poorly. They do not have a mind, so they do not mind being bored.

Al is maths, not magic. All AI is statistics and maths that can be broken down into algorithms so they are repeatable. Machine learning is the next step on the ladder, where the algorithms learn to recognise patterns. This takes trial and error, so that eventually, the machine can isolate common characteristics in a pile of data.

This is becoming more common every day, as we see uses for pattern recognition.

Both Google and Amazon have products you can download and use that deliver astonishing accuracy in pattern recognition. An occasional client has introduced this feature on his remote cameras, so they can now distinguish between a kangaroo and a truck, triggering a response from alarm connected to the camera, so the truck, potentially an intruder sets the alarm, the kangaroo which is more likely just hungry, is ignored.

The next step is usually called ‘Deep learning,’ and we are just at the beginning of this. It is in effect layers of machine learning interacting to identify from a broader and deeper pool of input data the item of interest. We will progress down this track, and at the end, in another 50 years, perhaps machines may be able to ‘sort of’, think.

This stuff all has the potential to make us seem smarter, but we are not, we are just using machines to do what they are good at, while we still do the stuff we are good at, empathy, judgement, relationships.

Over history, technology has created more jobs than it has destroyed. While it will be painful for some, there is no reason to believe the pattern will not continue. Irrespective of the size and type of organisation you belong to, AI is knocking on the door. Open it, realise the productivity benefits, and figure out how to best use it to serve others, and make a buck along the way.

Addendum April 2023. This post was over 4 years old when ChatGPT burst onto the scene, taking the world on a wild ride. In a post in December 2022 I asked essentially the same question, ‘Will HAL’ take our jobs? https://wp.me/p5fjXq-31n and arrived at the same answer. However, the gap of only 4 years has seen the development of the technology referred to above evolve at warp speed, culminating in ChatGPT3.

 

 

Future retail success will come from ‘Organic Intelligence’

Future retail success will come from ‘Organic Intelligence’

Oct 24, 2018 | Change, retail

 

There is some really interesting and contradictory stuff going on in retail.

On line shopping is continuing to expand at breakneck speed, so we are told. According to Statista.com the current percentage in Australia is 7.2%, but the percentage varies enormously from very little to an astonishing (estimated)  19% in China.

Small brands are being created, that rapidly become big brands, such as Shoes of Prey, that would not have been able to get off the ground pre internet, and bricks and mortar retail is struggling, going out of business at a rapid rate.

The latest casualty is Sears, the ‘Amazon’ of a former era, started in 1886 by Richard Sears, selling watches on the side of his day job as a railroad station manager. After the first catalogue was produced in 1896, to bring access to goods to the widely spread American population, Sears expanded geometrically. It was an entirely mail order operation, ‘analogue on line’ until the first store bricks and mortar store opened in 1925 adjacent to the distribution centre. The  following rapid spread of stores, saw the end of ‘Mum and Pop’ stores around the country, who could not compete with the range or prices that Sears offered.

Sound familiar?

Sears became a huge diversified business, accumulating a huge property portfolio as well as associated businesses and brands they owned, but it started to unravel in the mid 90’s, just as ‘Big Box’ retailers moved in, and the net evolved as an alternative channel.

Now we have Apple and Amazon investing billions in bricks and mortar stores, re-imagining them, but they are still bricks and mortar, and they are profoundly successful.  Apple, on a sales per square foot basis, the standard retail KPI, is the most successful retailer in the world. Amazon effectively acquired Whole foods for nothing, paying $US13.6 Billion for the chain, then seeing the share price rise in the following days by more than that amount on the back of the purchase. While Whole Foods is yet to make the expected profits, it is early days. On top of that you have Amazon bookstores and Amazon Go carving out a niche.

When the two most innovative and successful  retailers in the world double down on a business model, it might be worth a close look, and when it resembles an older model, but is clearly superior, that examination should be very thoughtful indeed.

The factor that has driven the success of Amazon, and all other on line retail, is Artificial Intelligence. The ability to write code that can trawl through mountains of data, identify patterns, and alter the output as a result of that recognition. They get better with use, but within the boundaries of the algorithms.  The factor that made Sears, and all other analogue retailers successful over the years, and has taken Apple to new heights, is the opposite side of the coin.

Organic Intelligence.

That ability of human beings to exercise empathy, and make connections an algorithm cannot yet make, and perhaps never will.

Apple and Amazon are learning to use both together,  and are streaking ahead as a result. Meanwhile, those legacy retailers who have not figured out AI are struggling, and more often than not, reducing their investments in Organic Intelligence as a short term means to reduce costs, so assisting in their own demise, as did Sears.

I wonder of any of the legacy retailers in this country will still be around in a decade?. To me it looks like the only one in the FMCG market that has demonstrated an understanding of the power of Organic Intelligence is Harris Farm.

 

 

 

 

 

How do you solve a critical problem?

How do you solve a critical problem?

Oct 12, 2018 | Change, Management

Define the problem first!

Dealing with problems effectively requires that  you first define the problem. This sounds pretty obvious, so obvious in fact that many do not think about it, they just persist with workarounds that address the symptoms, without getting to the core of the problem to solve it.

Not all problems are the same, so logically, they will not all have the same solution.

Classifying them in some way is a good first step, so here are four suggestions.

The ‘Cock-up’ Box.

Something or someone has acted in a way that is inconsistent with normal. There has been a cock-up. It could be a machine broke down unexpectedly, a customer delivery does not arrive, or a key component of a marketing program is missing, and many others. Point is, it is abnormal, so go looking for the root cause of the abnormality. ‘5 Why’ normally works very well in these circumstances.

The ‘Poor Process’ box.

The outcomes of a process done regularly seems to vary each time it is done, there is no reliable standard. The level of reliability is such that someone has to check or rework what has been done. I had a client whose MD routinely checked the detail of quotes done by his staff, looking for the errors he knew they were making, which he corrected, without taking any further action. Unless the process that enables errors of this type to be made is addressed, the problems will persist. Mapping what happens always helps to identify the ‘holes’. In this case, I ‘attached’ myself to a couple of quotes from the point they were initially received, mapping  the action taken, by whom, when, and what was the trigger, and created a ‘map’ of the process. It was then obvious to all where the causes of the variations occurred, and steps were taken to remove them. The result was a much greater level of confidence in the accuracy of the quotation process, which freed up a significant chunk of the MD’s  time to do more useful things.

The ‘Get Better’ box.

This often looks like the one above, but the motivation is different, it is often the result of an external pressure, resulting in a previously acceptable level of performance no  longer being acceptable. The typical examples are cycle times of all sorts of things being shortened, from order to delivery time, design time, response time, to improving the quality, however that is defined. In Australia, the example on everyone’s mind is the management of power. Costs have gone through the roof, and suddenly shaving a percent off the power bills here and there becomes an item of considerable priority, so effort is going into tracking and addressing all points of power consumption that can be modified to cost less, or be eliminated.

The ‘Out of the Box’ box.

As the name implies, this is where the ideas to address the emerging challenges are addressed. These are  innovations that you can either implement yourself, or responses to the trends observed that require big change. Having an established process to deal with and leverage innovation, significant improvements, unexpected situations, and opportunities that become apparent, is challenging. What it requires is a continuous focus on strategy and the long term vision, mission, purpose, whatever terms you use in your business. These things are way too easy to stick in the ‘too hard basket’ or the ‘will do it tomorrow’ basket, in the knowledge that tomorrow never comes without another short term crisis to address.

When you need assistance defining, then categorising the problems you face before developing solutions, give me a call.

 

 

 

Customer value conforms to the laws of Thermodynamics

Customer value conforms to the laws of Thermodynamics

Sep 24, 2018 | Change, Marketing

Theoretical Physicists disagree on a lot, but one thing they do agree on is that matter is constant, it does not disappear, it can undergo changes of form, and become something different, but is not destroyed.

Value is like matter, it does not disappear, it just undergoes change, and moves somewhere else.

Customers used to look for value in places where they no longer get the best return, so they look elsewhere to find it.

Technology may destroy some jobs, as it has in retail, and factories, but the jobs are not destroyed, they change form and move elsewhere.

For the last 20 years I have heard the ‘technology destroys jobs’ story, usually told by those with a direct interest in the industries being disrupted, in parallel to the number of jobs being created, usually touted by politicians with an agenda.

This is  not to denigrate the pain of those whose jobs are replaced by an automated process, but it does demonstrate the movement from one form to another.

Apple may have been a destroyer of jobs in some sectors, but they created many more in different locations, and in newly imagined retail as they re-created lost retail jobs in their Apple stores, now the most successful retailer in the world on a GM/Square foot metric.

If you take this perspective when thinking about the pressures on your business, and how it must respond to those pressures to survive, you just might be one of the fortunate ones who sees a picture of what the future might look like, and move there in front of the wave.

My favourite marketing strategist, Albert Einstein, once again, got it right!!

 

The 5 steps to optimise process development

The 5 steps to optimise process development

Sep 10, 2018 | Change, Management

 

Processes are the means by which we get stuff done, and are therefore an integral part of our personal and professional lives.

Mostly we just  allow them to evolve, usually in a pretty unthinking manner without much critical analysis. However, this is a mistake, as it leads to duplication, mistakes, omissions, personal idiosyncratic behaviour, and waste.

When valuing a business, one of the tell-tale signs of good management is the presence of a simple set of process maps which guide the way things are done, from the most mundane to the really important. This ensures, or at least makes the effort to ensure, that the same jobs get done in the same way every time, irrespective of who is actually doing the job.

The cost savings that result from this simple idea are enormous.

Creating a ‘process map’ or running sheet for the simplest to the most complicated process is pretty much the same.

The point however, is not to create a set of rules that can never be broken, it is just the opposite. A process to be optimised and improved  needs to be subjected to critical analysis on an ongoing basis, the written process just gives a stable starting point.

My experience with process mapping has involved 5 steps, that usually happen in an overlapping manner

 

Learn by observation and questions: Observe what happens currently, how things actually get done, consider the range of cause and effect chains in place, ensuring you do not confuse cause and effect with simple correlation. Go out and ask questions, seek insight into the hidden ‘wrinkles’ that exist in every process.

Experiment: An effective experiment requires discipline, primarily to test one thing at a time so you can accurately measure the impact of any change. The scientific method works: develop a hypothesis, test if it is true or false by collecting data, adjust the hypothesis and test again, until you find a hypothesis that holds true. As  Sherlock Holmes’s mentor said: ‘When you have eliminated the impossible, whatever remains, however improbable, must be the truth’

Codify: a process that remains in one persons head is no more than an opinion. To be effective the thought must be codified in such a manner that it can be accessed by anyone, and given the status of the ‘right way’ of doing something. I like visual process maps, they are easier to understand, and absorb quickly.

Distribute: once codified, the process needs to be distributed, and made easily available. There are now many digital tools around that enable distribution and simple reference. In the ‘old days’ processes would be in a manual somewhere that nobody looked at, even if they knew it existed. Nowadays there is no excuse, the process can be available to everyone with digital access.

Optimisation and creativity.  The paradox of all this is that with a stable process, you can now be creative, seeing alternative ways of delivering an outcome.  For improvement to occur you first need a stable system so the impact of changes are visible in measureable outcomes. This is the opposite to the chaos that people often consider to be a part of the ‘creative process’

Header acknowledgement:  Hugh McLeod at Gapingvoid.com