A fleeting associations with the facts and reality of what consumers demand is no foundation for long-term product development success.
In the cold light of day, consumers demand that product benefits improve their immediate, personal situation.
Consumers “pay” for products when the value of the benefit the product materialises, grossly outweighs the product price tag multiplied by the cost of adoption and use. The requirement for Value to exceed the perceived total cost significantly is the minimum threshold for product viability. That is the reality not just of the consumer, it is the reality of the world throughout history.
Modernity has not changed the implicit bargain between consumer and product. There have been changes in the scope of benefits and technology has improved the delivery. The form of payment in some cases has moved from fiat to information, especially in those situations where the consumer has undervalued their personal information. What has held over time is underlying calculation that the value of benefits must significantly exceed total cost, as viciously judged by the consumer.
The Balancing Act
To successfully sustain the product to consumer relationship over the long-term, entails balancing two different yet not incompatible demands.
1. Keeping the implicit bargain of delivering more significant and continuous value than the price tag which underpins the product’s revenue stream.
2. Craving out a competitive economic return within the confines of the product’s revenue stream. Product feasibility is achieved when these demands are in balance.
A product or product development endeavour which operates without acknowledging and applying a deliberate effort to balancing these demands exists separate from reality. Its market determination and sustainability becomes inextricably conflated with the faith and beliefs held by those who fund the fantasy.
So where does the passion, “the immersive consumer experience” and the delightful, friendly products which has become the mantra of product management practices, fit into this reality? The simple answer is that their necessities alone are not sufficient for a sustainable, prosperous product consumer relationship.
It’s commonly observable that successfully products do in fact have compelling consumer experiences. From that observation, comes the widely held and shallowly expressed belief in product management that a compelling consumer experience creates explosive product adoption and by extension, explosive revenue growth. Through this sequence of thoughts, the concept of “Sustainable Product Success” become conflated with“Compelling Consumer Experience”.
Compelling Consumer Experience != Sustainable Product Success
As a predictable consequence of the confabulation, the decision is made that the driver and navigator of the product development endeavour, should be orientated towards the pursuit of the “Compelling Consumer Experience”. Unfortunately, it’s a flawed decision for a few reasons.
Survivor bias colours the observations of successful products. We only see and read about those products that succeed. Many products with a “Compelling Consumer Experience” fail. The fact is less than 20% of all new products achieve any success. Furthermore, this has been the case since the late seventies.
The lack of proficiency in the quantification of what is a “Compelling Consumer Experience”, leads most practitioners down the path of working with that which is more familiar and tangible. They substitute product and feature design for the discovery, documentation, measurement and validation of consumer benefits.
By not crystallising a defendable expected value that the consumer could realise, work starts far too late on balancing Value, Price and Cost. This directly leads to not upholding the implicit bargain of the consumer demands.
This commonly seen pattern in product development endeavours is an inversion of cause and effect. The consumer demands a product must improve his or her situation at a price less than the value he or she places on that improvement. The consumer only becomes delighted when over time the gap between the Value of the Improvement and the total product price expands in their favour.
The size of the initial value to price gap influences the consumer’s perception of how compelling the product offering is. The first enduring cause does not occur until the consumer experiences the improvement to their situation. At this point, the implicit bargain is considered honoured. A consumers “Delight” is the effect of continuing to honour that Bargain over time while widening the gap between value and cost in their favour.
The final element of sustainability is the constraint product price places on development and operating cost. For those focused just on product and feature design, this aspect of product management delivers significant amounts of cognitive dissonance. This is evident by total avoidance of the subject area by those which should be most comfortable with it.
When a product strategy depends on such things as sustainable product offerings and consumer value, rather then propaganda, information asymmetry or market controls has a competitive advantage. Then employing a rational consumer benefit-oriented approach is the only viable option.
Those working on the product development cannot afford occasional interludes with consumer’s reality. They need to experience that reality and have a workable mental model that explains how and to what extent the product will improve the consumer’s situation.
The linkages between consumer pain, the benefits that targets the causes of the pain and the mechanism by which product features operate to eliminate or reduce those causes, require crisp quantifications of value and uncertainty.
A product remains feasible only when an acceptable return on investment continues to be the probable outcome, based upon credible projections with equally likely and unlikely revenue and cost ranges.
The credibility of a revenue projection depends upon:
- A probabilistic likely and unlikely estimate of the consumer’s valuation of benefits.
- A market size determined by a consumer-biased ratio on the benefit valuation.
- A probabilistic range of market share acquisition over the lifecycle of the product.
The credibility of a cost projection depends upon:
- The separation of product development cost and market share acquisition cost.
- Progressive, evidence-based probabilistic development through-put projections.
- Benchmarked market share acquisition projections.
Regardless that the realisation of a given benefit results in pure time-saving efficiency, access to new opportunities or information which delivers a competitive advantage. Once the outcome of the benefit is adequately understood and described, the benefit becomes susceptible to one or more of the quantification techniques. A defined Benefit without at least a notional quantification of value is a first indicator that the consumer’s reality is beginning to fade.
Benefit quantification is the first step towards embracing reality and being released from the dependency on belief and hope. A reasonable model can quickly starts to emerge based on the value that product is expected to deliver to the consumer. Using this model, product pricing becomes a function of benefit value rather than the average internet search for prices of similar offerings and a gut feel for “what a market will take”.
By continuously evolving and validating the consumer benefit value model, a credible revenue model can be assembled. Once in place, it is the cornerstone that supports every feature and product timing decision that is required. Having a revenue model that shows the ranges of revenue expectations under different scenarios along with confidence intervals, enables the defining of the (product) development budget.
Like the implicit bargain with consumers, stakeholders don’t want to make investments which are disproportionate to potential upside. It is worth clarifying the difference here between stakeholder returns based on growth in valuation versus product revenue and profit.
Blue sky, strategic positioning is a valuation multiplier influenced by revenue and profits, over which one has less tactical control as compared with product revenue and profitability. As improvements in revenue and profitability directly influences the valuation multiplier, it’s prudent and practical to focus our efforts on revenue and earnings.
The development budget guides the product development towards profitability. The central pillar of a budget is the dollar amount which can be consumed by development activities whilst maintaining the accepted probability of achieving the desired investment return. Let’s call this the “Maximum Feasible Investment”.
Maximum Feasible Investment does not equate to actual or expected development cost. It is merely the predetermined sunk cost level at which the probability of achieving the desired returns commences diminishing. Establishing the Maximum Feasible Investment level is critical to guard against the most significant destroyers of project value. Namely, incorrect assessment of initial feasibility and escalating commitments, which slowly and covertly erodes feasibility.
The first of these destroyers, “incorrect assessment of initial feasibility” is more common whilst the second “escalating commitment” is much more sinister.
Replacing Hope with Facts
Many projects which are not feasible or marginally feasible at commencement with all stakeholders confident in their success. As humans, even the most negative of us are hard-wired for hope.
That hope colours our assessment of feasibility, we ask only those instinctive questions which immediately occur to us (“How much is this going to cost to build?”). We attempt to create certainty as a path to determine feasibility. Instead, we should embrace uncertainty and think in orders of magnitude.
To elaborate on this, let’s take a simple example of a feature set within a product that is expected to generate just under two million dollars of lifetime revenue in present dollar value.
In arriving at lifetime revenue, the product team has considered the real value of the benefit that the feature set will provide to the consumer, which by definition is considerably more than two million dollars. As a diligent product team, they also have determined the range of cost to acquire them given a certain number of consumers to deliver the lifetime revenue, benchmarked as being between 12% to 20% of the revenue.
We accept that assuming the above revenue side survey has been conducted, is not alway true. For sake of this article, let’s assume it is in place and has been executed well.
The first significant error in determining feasibility occurs typically early on and takes the form of what appears to valid question.
With the best of intentions the question is posed:
How long/(how much) will it take to build envisioned feature set?
Motivated by the instinctive desire to reduce uncertainty, a tremendous amount of time and energy gets wasted generating an answer which is always more wrong than right. It’s an answer that also often has unintended consequences as acting a bias anchor for later expectations and unnecessary closes off alternative designs and implementations which could better deliver the desired benefits.
Is this not an impasse on the feasibility question? It feels like we need to know this before we take another step. Well not really, we don’t need perfect information in this situation. We can work with what we know to determine how much more information we need to proceed.
Starting with the knowledge of the benefits which we identified, we know there is a range of possible lifetime revenue outcomes. Factors identified in the benefit value model influence the width of the revenue range. On the low side the lifetime revenue could be just $950K, yet with alternative pricing levels and adoption rates, lifetime revenues could reach $1.2M, $1.6M or $1.9M.
Using these alternative outcomes, we can build a probability distribution for expected lifetime revenue. From this distribution, we draw out a revenue range aligned with our risk appetite. For this example, we will accept odds between 1:1 and 1:3, so 50% to 75% probability. These odds translate to an expected lifetime revenue range of approximately $1.5M to $1.8M. Applying the same approach towards consumer acquisition cost, we end up with acquisition cost that ranges from $235K and $245K.
Deducting the cost from revenue, this indicates that there is an even or better chance of earning $1.3M to $1.5M from providing the benefits to the consumer. Given a desired return on investment of say 30%, the “Maximum Feasible Investment”, under these conditions, is in the range of approximate $920K to $1.1M.
Our feasibility question now changes to:
“How probable is it, that a feature set could be developed within the limits of the ‘Maximum Feasible Investment’ that delivers the expected benefits?”
The answer to this question is adequate to determine the immediate fate of the proposed benefit. It also has the characteristic of eliciting a quicker, more likely to be correct response.
By just using “Maximum Feasible Investment”, we gain adequate data to eliminate those proposals which are overtly not viable given the reality in which the development is occurring. We also eliminates the demand for effort estimates, at a point in time where such estimates are known empirically to have an error margin of plus or minus 200% to 400% whilst disadvantaging development endeavours before they have even gotten underway.
Historically, project feasibility test or go/no-go phases and gates have been introduced to combat the escalation problem. Escalation is evidenced by projects which expand in scope and resources despite offering no real prospects of payback. Naturally, escalation contributes to waste; hence the past efforts and current management techniques attempt to control the behaviour.
Besides the current approaches being impractical, they often create a demand for effort estimates, at the exact point in time, when it unsafe to do so.
No empirical evidence exist showing escalation prevention tactics have been useful.
In the field of software development, we know that 30% to 40% of all projects escalate despite current tactics and practices to prevent such escalations. Furthermore, the projects which do escalate, they experience significantly more performance and delivery problems.
The causes of escalation are rooted in our cognitive perception of risk, sunk cost biases and by cultural dispositions. More practically, the absence of specific factors increase the likelihood of escalation. For example, a development endeavour that is not able to discern at any point in time, if they have achieved consumer benefit materialisation, is 21 times more likely to escalate. Developments without timely access feasibility data are 10 times more likely to escalate.
Maximum Feasible Investment affords reuse here, as a reassessment trigger that can be applied to short-circuit escalations.
Not all products will be winners; this is the way it should be. What is not acceptable is discovering a product is not a winner too late and not having any available options or tools do anything about it.
Guiding the development of a product towards a successful outcome requires us to face reality by making a demonstrable argument of benefit value and by extension economic viability. The knowledge and tools for doing this exist. We just need to apply these within the context of our consumer’s reality, so we are able to balance the implicit bargain that they demand.
The concept of Maximum Feasible Investment we have discussed here is no silver bullet to tackling the uncertainty in product development. It is a specific tool that targets a narrow part of the real world challenges of developing a sustainable and successful product. Used alongside tools like Benefit Quantification, Benefit Failure Probability and Development Throughput Optimisation, uncertainty can be focused, to allow the alignment of the consumer’s reality and economic reality. Allowing the developed product to strike a bargain with it’s consumers which leads a sustainable profitable future.
Striking and maintaining the bargain demands your continual focus on that bottom line.
This is not easy with so much noise attempting to unbalance the calculation. So do yourself a favour, take a pass on hope, belief and silver bullets; tie yourself to the strongest heaviest anchor you can find and firmly tether it to the consumer’s reality.
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