“Intellectual Capital on demand”.

This is a term coined by Peter Drucker when talking about contract management, particularly in relation to older contractors who bring a wealth of experience and hard won wisdom to the table.

Using contractors, particularly high level ones brings a number of huge benefits:

  1. Turns a fixed cost of an employee into a variable, project specific  cost.
  2. Easier to impose specific performance measures, as the responsibility of the contractor is to the task, and less to the cultural environment.
  3. They bring immediate resources to projects otherwise difficult to staff
  4.  Offers the flexibility for enterprises to bring in specific skills from time to time, that they do not need all the time.
  5. Generalists, and those with a wide experience, are better at seeing how logically unrelated pieces may fit together, they are less concerned with ambiguity, than specialists, and less likely to “anchor” an analysis in their specialty, and narrow perspective.

Our economy is undergoing structural change, management productivity is under scrutiny, so it makes sense for businesses, from start-ups to huge multinationals, to take advantage of the big pool of highly experienced, mobile, and motivated older contractors.

Category management steroids

Data mining as it is evolving in retail is a fascinating exercise in identifying behavior characteristics that apply to very small percentages of the shopper population, and doing something with them. Progressively retailers are getting better at leveraging the data, and as the penetration of cards increases past a critical mass, so will the effectiveness of the marketing and promotional programs. Of course, consumers are well aware of this, and have well developed “relevance meters” built in.

Consider the category management of potatoes. Pretty dull stuff? no, fascinating stuff.  I am making these numbers up to illustrate the point, but consider, of 100 customers using their cards at the checkout,  perhaps 10% have potatoes in their trolleys, and 10% of that 10% have a particular variety, and of that 10% (now down to 0.1%), they also have sour cream and chives in their trolley.  Pretty reasonable guess that the potatoes will be cooked in their jackets, with sour cream and chives garnish, particularly if the shopper is single, no kids, and also buys steak.  An opportunity to offer the consumer a deal on a bottle of red wine on her way out of the shop, or in the associated retailer across the way? Multiply that by 5 or 6 million cards, and you have a pile of data to mine.

The gold standard of retailer card data mining is Dunhumby, now owned by UK retailer Tesco. They did such a great job in the development stages of the Tesco loyalty card, that the retailer bought them to keep their competitors away from them. In a move that recognises the future, Dunhumby is now crowdsourcing ideas via Kaggle, a fascinating startup that turns data mining into a competition for data nerds.

This is Category Management on steroids, and represents a monumental change in the skills needed by FMCG suppliers deal with dominant retailers. In the Australian context, very few FMCG suppliers have any idea of the power of the data tsunami coming at them, and how this will impact on their brand marketing strategies. It is also the realisation of the vision of category management the few of us who were playing with this stuff  30 years ago had when the data was warehouse withdrawals, we had a bit of U&A consumer research, and managed it all with calculators.

Technical & Creative, + the best ad of all

Today in Sydney has been about as miserable as it gets. Rainy, cold, grey, just plain shitty, and not fair for a public holiday.

What a relief it was to find a distracting way to spend the afternoon.

After watching the replay of the unfinished French Open final, assiduously avoiding any media when I “rose” so I did not know the score, I started to clean up the hard drive of my laptop, removing some of the stuff that had accumulated to clog it up.

Amongst the “random savings”,  were quite a number of advertisements I had accumulated from various sites, all of which had the common element of having struck me at some time as being enormously creative, funny, engaging, delivering a serious message, or just sufficiently different to really cut through, when flogging stuff from cars and fashion to condoms and computers. They all, in one way or another, rang my creative bell.

It also struck me that we are in the middle of a huge confluence of two enormously powerful forces, technical development, and creativity, that is changing everything. Hardly an original insight.

The technical advances of the last 15 years  have reduced the costs of technology, and the distribution of content to relatively miniscule proportions, which has opened up huge new opportunities for creativity to be seen. However, the digital media has become so clogged with content, from the great to the absolutely inane, that being seen is still the greatest challenge, so creativity remains an essential element of all successful communication. It has also offered up the opportunity to focus laser-like on a very small group of individuals, delivering a compelling message that they would have been unlikely to get in the old mass communication days. 

I cannot finish without offering my pick as the best ad of all time, at least the best I have seen.  Perhaps surprisingly, it comes from my childhood, so is a very old ad, but is a very simple execution delivering a powerful message in unequivocal terms.  Pity the companies management was not up to same standard as their communications people.

7 steps to Data Literacy.

Anyone who can read can read a Keats sonnet, but not everyone can “see” the lyrical quality, and feel the passionate introspection most have at their core. Those who can are truly literate in English poetry.

Data Literacy, a term I like, similarly implies not just an analytical capability, but also an intuitive capacity to understand the nuances and hidden gems in data, rather than just the capability to be informed by apparent outcomes.

Have you ever seen people making stupid decisions while pointing out that the data justified them?

I see it all the time. It seems to me that there should be a knowledge building chain here, rather than just a data analytical one:

    1. Gather data,
    2. Analyse data,
    3. Apply healthy skepticism to the outcomes,
    4. Gather more, preferably counter intuitive data,
    5. Pursue the trends, outliers, inconsistent data, apply informed analytics rather than statistics,
    6. Synthesis of the complex, often paradoxical information,
    7. Informed intuition, and data literacy evolves.

Not all numbers are equal, some are more reliable and informative than others, simply because they are the result of tested assumptions, and more and better informed questioning. The development of literacy takes time, effort, and resources, but is worth it.  

2 parameters & 5 measures of optimised processes

Robust, repeatable, and easily taught processes are the foundation of good outcomes. It therefore makes sense to consider the factors that separate good processes from poor ones, the effective from the ineffective.

The measure of the process has two parameters:

    1. Repeatability. The outcome is repeatable, it has become the way things are done, so has an element of “automatic” about it.
    2. Agility. In apparent contradiction to the above, effective processes must also be sufficiently agile to accommodate the short term stuff that just happens, and flexible so that they can evolve to continue to deliver optimum results in response to the changes in the environment in which they operate.

Over 35 years of participating, observing and analysing processes, there appears to me to be a small number of enablers that drive effective processes. The weighting of these factors is different from situation to situation, but all are evident to some extent in every successful location.

  1. Deliberate Design. Successful processes are the outcome of a deliberate design. Sometimes the design comes after a process has evolved, and it is modified and optimised post birth, other times, the design is a deliberate response to a situation that requires a process.
  2. Infrastructure support. Processes do not survive in a vacuum, so the organisational and operational infrastructure, and the culture of the organisation play a significant role in their success. Without any of these three infrastructure foundations, a process will become sub-optimal.
  3. There is an “owner”. This is just another way of saying that someone in the organization takes specific responsibility for the effective management and support of the process. The more important the process, the more senior the process owner should be. In almost every situation, a process adds to other broader processes, and each component should have its own owner. Eg. An inventory management process has many sub-processes, from the documentation of deliveries to the appropriate allocation of purchase order numbers and general ledger postings. The “Inventory Management” process may be owned by the CFO, but the supporting components will be owned by others at the more operational levels.
  4. Process metrics are in place. The old saying, “you get what you measure” is accurate, without performance measurement against current criteria, as well as some that may reflect how the organisation expects the process to evolve, it will solidify at sub optimum performance levels.
  5. Process improvement. Continuous improvement of processes is a feature of successful businesses, the environment in which businesses operate is subject to ongoing change, and therefore the enabling processes need to evolve to best reflect the environment.  In an apparent paradox, improvement is really only possible in a situation of stability. To improve a process you need to be able to identify the impact of a change in the process on the outcome, and you can only do that when the impact of all the existing variables are known.

Bust the mould.

On a flight from a regional town last week, the attendant went through the nonsense of the “safety speech”.  Instructions on how to do up the seat belt as if nobody knows is pretty dumb, but of total irrelevance is the instructions on how to use the life-jacket. I remain unconvinced that a little whistle and light will do much good if the engine stops at 20,000 feet, and the only water within 100km is in farmer Browns property dam. What about a parachute?

However, it is all taken so seriously, passenger jokes are not appreciated at all. Surely an example of a mould that needs busting.

Another mould more likely to be busted by the avalanche of mobile and electronic payments innovation is the banks credit card and cheque business model. 

I have observed the missed opportunity by banks before, and the pace of change is accelerating rapidly picking up as Apple, Google, Paypal, and a host of startups like “Levelup” “Square” see the opportunity in disruption, and are chasing hard, often using technology that evolved in an ecosystem with nothing to do with banking. 

These changes pose a huge problem for banks, one that their legacy structures and business models are apparently having big problems addressing.  The role and performance of banks around the world over the last decade, and in the current European mess has removed any residual loyalty consumers may have had, and opened them up to non bank competition that will change the nature of banking in the coming decade.  Opportunities abound to bust the current mould.