The last 10 yards.

Independent produce retailers appear to be resurgent, based on the quality of their offer to consumers.

For years anybody who has been involved with FMCG has known about the challenge of the “last 10 yards“, the distance between a supermarkets back dock and the selling face. Retailers talk about out of stocks, and lost sales, suppliers struggle with short lead times, demanding delivery schedules and the lack of accurate and collaborative forecasting.

Added to these are these challenges presented by fresh food, perishability, appearance, consumers determination to handle and “cherry-pick” the produce, and the nightly put-away. The major supermarkets would appear to be losing share to resurgent independents, as they have responded to the supply chain challenges with greener fruit, more resistant to damage, and offering a longer period to maximise the opportunities for sale. Downside is that green fruit is not much good to eat.

Produce is a difficult category where training and product knowledge is more important than in any dry grocery category by a mile. Why then are there casuals in produce? Last week I saw, not for the first time, a seventeen year old tipping a box of tomatoes onto a display like they were Lego bricks, surely some training would be useful? In this case, it was the last 10 inches that stuffed the tomato. 

No wonder specialists who know their business, and can manage the challenges particular to a category are doing a better job than generalists, and consumers are responding.

 

Statistics and thinking

A statistical analysis should give a black and white answer, and it does, but the answer is only as good as the information that is used, and the manner in which it is used.

It follows then that the application of analytical tools should be in the context of a way of thinking through problems, evolving and testing solutions, and connecting the resulting processes in such  a way that they deliver repeatable solutions that deliver positive outcomes.

Statistics are not very useful with out the support provided by creative and insightful thinking, and such thinking is uninformed without the benefit of the analytical foundations of statistics.

Sometimes it all gets too stupid, as was the case during the resources tax debate prior to the removal of Kevin Rudd. Formerly reputable KPMG had done two studies on the tax, one for each of the protagonists, and ho, ho, who could guess, comes up with  two opposing answers that just happen to support the opposing views of those who commissioned the studies.

This laughable tale highlights the paucity of real thought that went  into the debate and the nonsense value of financial modeling without the supporting rigor of thought, and it goes on. The deal now done reduces the tax take on paper far more than the number  put out by the government, the numbers simply do not add up, and it is easy to assume that there has been some more creative assumptions built in to alleviate the political heat associated with another “back-flip”.

Who would ever believe “financial modeling” again.

Cash for suggestions – is it necessary?

Many businesses offer cash for suggestions, put a suggestion box near the canteen, and wonder why most of the suggestions  are physically impossible, morally debatable, and often both.

In the end, successful suggestion programs offer the reward of personal satisfaction and recognition to those making them, any financial incentive is usually secondary. The $50 in the paypacket for a successful suggestion is nice, usually appreciated, but not the reason the suggestion was made.

People who are members of a “community”  and a workplace is a community, normally want to contribute to that community, unless it is dysfunctional in some fundamental way, and those contributions build connections and mutual obligations, that are the glue of any community.

Many suggestions will be worthless, but offering recognition and feedback to all offerings creates a sense of personal connection. Create that, and the suggestions will increase in value progressively, and ultimately, very few will have anything to do with deviant behavior, and you will quickly be able to do away with the anonymous box, and have the feedback directly, person to person.

 

It would be nice to know

Now there is an explanation for the common situation where a person fails to see what to others appears to be blindingly obvious.

The Dunning-Kruger effect provides the psychological evidence supporting what most of us see often, and that is that our (and others) incompetence in an area masks our ability to recognise that incompetence. The “we don’t know what we don’t know” effect at work. 

When you think about it, the absence of the skills we need to recognise a right answer when we see it, are the same as the skills required to produce a right answer in the first place. This makes sense when you read it twice.

Our exertions as we consider complex issues, from the future of the financial depredations of the GFC on the economy, to climate change,  what to do about our involvement in Afghanistan, to the personal questions we all face, are all about making decisions today on the basis of our understanding of the  best information we have available, but often misunderstood, misinterpreted, and often misused or ignored.

We therefore most often make those decisions in relative ignorance, seeking easy, saleable “solutions” to problems where we are ignorant, but unaware of it, or unable to concede it.

How scary is that?

Data and useful information.

    Working with a relatively new client recently, I was very impressed with the data that was available, but bemused by the almost total absence of productive use that was made of it.

    It became obvious pretty quickly that most of it was produced by rote, and there was no real thought given to the costs of producing the data, how it would be used, and the value that it would add, it was just done, because it had always been done, the original reasons for collating the data lost.

    The exception was a suite of reports provided to the MD and executive team that went into minute detail, and took several people 2 weeks to produce each month, and created great angst because it provided a platform for allocation of blame, and caused great focus on the month gone, with little or no regard to what may happen in the future.

    To assist making a change, we went through a process of rating the data on 4 simple parameters:

  1. Are we collecting data that will be used to answer questions that are worth asking?
  2. Does the data assist us to look forward, or is it just about yesterday?
  3. Do the individual pieces of data contribute to developing the larger picture of what is happening internally, and externally that we should know about, and what gaps are there? 
  4. Is the data just quantitative, or is there a qualitative component that is adding to the story?
  5. This simple list created some vigorous discussion, both about the relevance of the list itself, and the scores given to the data collected, but the outcome is a much smaller, user friendly suite, tailored to the needs of different functional management, that takes much less effort to assemble, enables intelligent review of performance, and is the basis of planning and decision making.

     

Challenge of the first.

    In this digital age, the first contact in most situations is digital, where the marginal cost is approaching zero.

    This simple fact has changed the sales cycle, as this contact can evolve into an offer to become closer, or it can become a barrier, but each party understands implicitly that the rules have changed.

    The question now is not one of how quickly can a sale be closed, or indeed, the process brought to an end, there is more dancing involved, largely because the dancing is cheap, non threatening, and easy. For a sales organisation, there are a few simple  questions:

  1. What sort of digital tools do we need to engage key prospect groups?
  2. How much time and effort should be spent on developing a sale before we reach the go/no go point?
  3. How much do we need to give away?
  4. “Give away” now more often than ever strays into the arena of proprietary IP, as  efforts to differentiate and add value in a commoditised world accelerates