Oct 21, 2024 | Lean, Management
Seeking highly efficient processes is the holy grail of most operational managers.
Is it the right goal?
‘Garbage in.. Garbage out’ still applies, even if the garbage gets a slick coat of paint on the way through.
The process as implemented might be efficient, optimised, but does it deliver the outcome in the most effective way?
A typical example is from a while ago when the NBN was (compulsorily) connected.
The technician turned up just within the time window, to do the connecting work, and did it quickly and it seemed, efficiently.
After about 45 minutes, he informed me it was all done, all I had to do from there was connect up the modems around the house.
When I expressed surprise, that until everything worked, the job was not complete, I was told: ‘Not my job, I have 7 connections today, and I am behind by almost an hour’.
Clearly there was an optimised process of installation by NBN subcontractors in place, the final few feet being the responsibility of the retailer. However, as far as I was concerned, I had paid the compulsory $172 for ‘connection’ and it was not complete until everything worked.
It may have been an efficient process from the perspective of the NBN, but from the perspective of someone who had paid for a service, it sucked.
The technician was prevailed upon to ensure that the job was complete, to my eyes. The problem for him was he failed to meet the stupid KPI imposed by someone seeking an efficient process, rather than one that optimised the outcome.
Header image is obviously courtesy of AI, and is therefore not optimised by a human.
Oct 18, 2024 | Communication, Customers, Marketing
The sales funnel, often depicted in materials promising a path to riches, has profound flaws.
It implies two misleading concepts:
Gravity: The notion that business arrives at your door via discrete steps in a gravity-driven funnel is nonsensical.
No customer focus: Until the bottom of the funnel, where deals are signed, the emphasis is on marketing tactics rather than the customer.
Success demands that a customer is willing to pay for a need to be filled, an itch scratched, or an aspiration fulfilled that’s worth more than the price paid. Value must be created for the customer.
Even for everyday consumer goods, not everyone is in the market all the time. For most products, consumers are only occasionally in the market. In B2B sales, buyers may only appear once a decade, and they’re often not the ones who ultimately make the decision to buy and authorise payment.
These factors lead to the conclusion that the standard templated sales funnel is fundamentally flawed.
My alternative, displayed in the header, is more realistic. It shows progression through a sales process powered by the quality of attraction at each point. It starts with the customer being in the market only occasionally. At those times, you must be included on their list of possible solutions, usually weeded down to a shortlist for further investigation.
At each stage, customers face friction, go/no-go decision points, as they move towards a transaction. Your marketing collateral and overall impression contribute to overcoming this friction. For example, a potential car buyer will suddenly notice many shortlisted brands on the roads simply because they’re now aware of them.
This process is called the “frequency illusion” or its formal name: the “Baader-Meinhof phenomenon” (A scary name for those over 65.) It involves two related psychological concepts:
- Selective Attention: Once aware of something, your brain automatically looks for it, making it more likely to be noticed.
- Confirmation Bias: Encountering the thing you’re now aware of, your brain notices it, making it seem more prevalent.
Templated sales funnels tend to oversimplify the complexity of a customer’s journey towards a purchase. They rarely accommodate the differing behaviours of potential customers, lack recognition of the reasons one prospect drops out, and others circulate between stages as they reflect on the purchase. They completely ignore the impact of competitive activity and offers that may emerge, and tend to emphasise quantity over quality of prospects gathered.
By starting at the exact opposite end, where the potential customer lives, you should be much better able to craft marketing collateral and action points that reflect the real position in a purchase journey of a prospective customer.
Oct 14, 2024 | Analytics, Marketing
Against my better judgment, I recently engaged in a conversation about the ‘Law of Purchase Duplication’ with a young marketer. He seemed quite convinced that he was delivering a groundbreaking insight to a marketing dinosaur.
In essence, the law argues that the larger a brand’s market penetration, the more likely a consumer is to purchase alternative brands within the same category. Smaller brands, on the other hand, struggle with loyalty, relying primarily on occasional or incidental purchases when they fall within a larger brand’s ecosystem.
This concept, while not new, remains fundamental to understanding brand dynamics in the marketplace.
Back in the day, we referred to it as the purchaser’s ‘acceptable pool of brands.’
This young hot shot expanded on the advantages of being the dominant brand, and how it becomes self-sustaining through positioning, weight and quality of advertising, brand salience, product accessibility, and consumer perception. While this may all be true, the notion of it being ‘self-fulfilling’ is a step too far.
The reality is that maintaining market dominance requires constant effort and adaptation to changing consumer preferences and market conditions.
During our discussion, the topic of brand loyalty surfaced, leading to several useful questions about what brand loyalty truly means in today’s fast moving consumer markets:
- Does it mean that no other brand will ever be purchased under any circumstances?
- Does it only matter when a preferred brand is unavailable?
- Is there a sliding scale of brand loyalty that correlates to price differences?
- How does this law of duplication apply to sub-categories within the same brand?
- What are the varying impacts of demographics and psychographics of consumers?
- Could brand loyalty simply be a combination of awareness and preference, disconnected from actual purchasing behaviour in-store?
These questions highlight the complexity of consumer brand loyalty and the need for an understanding of the nuanced drivers of consumer behaviour in every market.
Over the years, I’ve been intimately involved with several instances where this so-called ‘Duplication of Purchase Law’ played out in real-world brand battles:
Meadow Lea Vs all comers. The rapid ascent of Meadow Lea margarine in the late 70s and early 80s was astonishing. The brand evolved from one of many competitors to a market leader, at its peak dominating with three times the market share of its nearest rival. Although it was driven by exceptional advertising, there were several alternative brands consumers could have turned to. However, consistent availability, competitive pricing, and in-store sampling helped cement its position. These instore marketing activities supported the brand advertising that built long term brand salience and loyalty.
Yoplait Vs Ski. The yogurt wars between Yoplait and Ski during the 80s and 90s are another example. Yoplait initiated huge market growth by making yogurt mainstream when it launched. This left Ski, the previous leader, floundering and scrambling to recover. Both brands became largely interchangeable despite product differentiation. Yoplait strawberry was an acceptable alternative to Ski strawberry, and vice versa. However, this dynamic didn’t extend evenly across other flavour categories or packaging formats. If Ski strawberry was unavailable, Yoplait strawberry was more likely to be purchased than an alternative ski flavour. These inconsistencies across the product categories and pack sizes, highlighted how nuanced and context-specific the Duplication of Purchase Law can be.
Having reliable data from the likes of Ehrenberg-Bass provides the statistical credibility necessary to sell what to date have been qualitatively understood wisdom, to the boardroom. However, it’s crucial to remember that this qualitative wisdom, built over time, should never be discarded or obscured by academic multi-syllable descriptions or management jargon. One-dimensional data cannot replace the wisdom accumulated by thoughtful marketers over time.
Oct 11, 2024 | Analytics, Operations
Real-Time Feedback is the objective of any effective performance management system. We instinctively knew how to generate and leverage feedback as kids. Remember that cricket scoresheet a parent kept during a Saturday morning game? It could just as easily have been netball, hockey, soccer, or footie.
Every ball bowled was accounted for in real-time: a run, a wicket, who bowled the ball, and who was the batsman. This real-time recording enabled tactical choices at every ball. This is a ‘box score.’
By contrast, typical accounting systems look at what’s happened up to a point in time, often monthly, in arrears.
Translating real-time game results to a commercial context makes perfect sense. It enables decisions on a short-term basis that maximises outcomes.
Adapting to this change isn’t easy, as our accounting training, established processes, and regulatory systems are geared to historical data, not real-time. They use ‘standards’ and reporting templates that obscure real-time detail.
Successful businesses find ways to translate the outcomes of their actions into visible measures of real-time performance from which they can learn, iterate, and improve.
Following are six tactics you might consider implementing to improve your performance.
-
-
- Break down your processes into their component parts, as far down as you can.
- Identify the bottlenecks in those processes. These usually become obvious the further you break the processes down.
- Choose the two or three key metrics that track performance of that part of the process, make them transparent via dashboards, and give the operators the power to adjust and improve.
- Leverage technology to both do the measuring, and providing the real time feedback. This can be a simple as a digital display of unit movement down a production line, or sales orders received.
- Start small, and build as the ‘performance bug’ bites those involved. Achieving this sense that there is a ‘performance bug’ around is a function of the leadership and resulting culture that is built.
- Integrate the dashboards in a process I call ‘Nesting,’ so that each board builds on the ones that contribute to it. For example, a dashboard that reflects the units going past a specific point in a manufacturing process, build to one that reflects the output of that specific production line, which builds to a factory wide dashboard.
This is all easy to say, but very hard to do. However, if it was easy, everyone would be doing it
Header credit: Wikipedia. The scoresheet in the header is the scoresheet of Australia’s first innings in the Ashes test against England at the Gabba in 1994. Michael slater scored 176, mark Waugh 140, and Glenn McGrath did not disturb the scorers, shooting another duck. A perfect example of a ‘Box Score’.
Oct 8, 2024 | Analytics, Innovation, Strategy
Have you ever been in a situation where you just ‘know’ a course of action is right?
No data, no detailed scenario planning, you just know.
I have.
Where does that confidence come from, and is it justified?
Have you distinguished between genuine intuition, based on experience and knowledge, and the overconfidence that can arise from a lack of awareness of one’s limitations?”
In my experience which includes choices that have been both very good, and very poor, there are two qualitative drivers of those good choices.
Significant domain experience.
This experience does not come from being around for a while, it comes from taking action many times, and learning from the outcomes, resetting, and trying again.
For example: a seasoned chess grandmaster can often intuitively anticipate the best move without consciously calculating every possible outcome, drawing on years of experience and pattern recognition.”
Learning from analogy.
When you see a course of action succeed in other domains that have some similarity to your own, you can infer that the success may be repeatable in yours.
For example: The introduction of disc brakes in cars came from their development for use in stopping aeroplanes when landing.
In a world increasingly dominated by data, it’s crucial to remember that while numbers provide valuable insights, they should not be blindly trusted. True wisdom often lies in the delicate balance between data-driven analysis and the intuition honed through experience and learning from mistakes.
Chess is a game where a grand master has a store of intuition gathered and sorted by years of practice that is leveraged instinctively when playing.
