In our first article (part 1) we described what digital transformation play might be most relevant to a business based on what part of the business was the constraint. In part 1 we glossed over how we ascertain what the constraint is. In part 2 we’ll be looking at this in much more detail.
A note on prioritisation
This article is about what I consider to be one of the top issues facing business today — prioritisation. Modern businesses (in my experience) regularly (if not uniformly) take on too much work, underestimate effort & complexity, and lack an enterprise-wide approach to prioritise what work they have committed to. This article doesn’t solve (entirely) for prioritisation, but does help direct prioritisation efforts, particularly as they relate to digital transformation.
A constraints-based (enterprise-wide) approach to prioritisation
Theory of Constraints (ToC) dictates that to maximise throughput we must identify and elevate the system constraint. In basic systems (with few processes) this can be relatively straightforward, in large enterprises this can prove to be more complex. To create a proxy for this we imagine the enterprise as one process — i.e. the business process we outlined in part 1.
From a prioritisation perspective, we want to focus enterprise efforts more squarely around the area of the business constraining our throughput — for the purposes of high-level prioritisation we recommend translating throughput into Customer Lifetime Value (CLV).
Once we’ve identified the area constraining CLV, we can re-prioritise global efforts to elevate this constraint.
Why prioritise this way? An example…
Imagine an organisation that has chosen to prioritise efforts around marketing — believing that brand awareness is holding them back. They invest heavily into a new campaign, that significantly raises awareness and then flows through to new leads — more than a 50% increase on the previous period. What they didn’t realise is that sales only had an extra 10% capacity — essentially wasting 40% of that increase — and hence wasting a significant investment, upsetting customers and creating bad press in the process.
While a basic example, it helps demonstrate the simplicity of the concept. Clearly (especially in larger organisations) measuring the CLV at each stage is more complex!
Why CLV as a measure of throughput?
The measure is (somewhat) arbitrary — and depends on the goal of the organisation. My argument for CLV is it represents value for the business now and into the future (in line with The Goal). If your organisation chooses customer satisfaction as your goal, you may choose to use a measure like NPS.
Calculating CLV at each stage to help identify the constraint
At each stage in the organisation, we can use average conversion rates to determine how much of the total organisational CLV is passing through each stage (at any given time). More importantly, we can start to estimate how much additional investment might improve this conversion and hence affect overall CLV, giving us an indication of which stages represent the best ROI opportunity.
I wouldn’t get too caught up trying to measure this perfectly. Remember the reason for doing this is simply to identify what area to focus transformation efforts on. Proxy values should suffice unless the values are very similar in multiple areas.
In terms of how to calculate CLV this will vary from one organisation to the next. I’ve put a practical example into Part 2.1 (see further below) — but please don’t take this as gospel — it’s just one way you might choose to approach.
So we’ve identified the constraint… what next?
Let’s assume you “cracked the code” for estimating CLV (good for you!) — now we’re back to Part 1 — time to choose your Digital Transformation Play and get to work 🙂
Of course this is just the next step. Assessing your organisational throughput (and identifying the constraint) is something that should be done regularly.
For a more in-depth example on assessing CLV and identifying constraints (and more detailed prioritisation) please see Part 2.1 — Calculating CLV (a practical example) below.
Part 2.1 — Calculating CLV (a practical example)
To help demonstrate how calculating CLV might work, let’s imagine a t-shirt E-Commerce store… here are the steps to follow:
Step 1: Let’s assess our Customer Lifetime Value (CLV)
Once again, let’s not get too caught up in the science of getting this metric perfect. In our fictitious store, we have 40,000 customers spending an average of $75 per year. The average customer lifetime = 3 years. So the customer lifetime value is 3 x 75 = $225.
Step 2: Determine how each stage contributes value to the process
Essentially being one large (and organic) funnel, we want to understand how each stage converts, and how this compares to average (and “best practice” — but more on this later). Let’s compare these now.
What the above table does is estimate how much value each extra individual (in that stage) contributes. In the design stage, we can see that expanding our market by one extra individual contributes very little extra value. This should intuitively make sense. But if we expanded our offering to be relevant to an extra 1,000,000 people – well that would be significant!
For each stage, you’ll see that the total value contribution at each stage is the same. This is because we’ve set this snapshot in time as our benchmark.
Step 3: Compare results to benchmarks
If we change our benchmark (to monthly average or industry average, for example) then things get a little more interesting.
Adding in benchmarks for our monthly average (over the last 12 months) starts to reveal something more interesting. And starts to give some better insights into business constraints.
For each stage, we compare this months performance vs. our 12 month average vs. industry benchmark. This tells us a few things: a) where things are generally improving (or not), and b) how our business performs against the industry. Remember, just because an industry has a benchmark it doesn’t mean we shouldn’t aim to exceed it. And likewise, there may be good reasons or circumstances why we can’t reach these benchmarks. But painting this picture helps us a understand where we sit, and by comparing the opportunity vs. Market (plus our historical performance) we should be able to identify the constraint and move forward.
NOTE: We also want to note the utilisation rates for each stage, particularly where there is manual “processing” required. As a practical example, if your business requires salespeople (or Business Development Managers etc.), and these people are legitimately working 40+ hours per week, then your Decision stage is at 100% utilisation. And any attempts to make improvements further up the funnel, without increasing this utilisation, will typically prove fruitless.
In this example, we can see there’s a lot of latent opportunity in the Deliberation phase (where we’re performing below our monthly average AND the industry average), but not so much in the Decision phase (where we’re performing both ahead of our monthly average AND the industry average).
The dollar amounts (for monthly improvement and industry gap) represent how much extra we might make per month by bringing our conversion back in line with either our own historical average or that of the industry. The focus value takes the difference between those two amounts — factoring in that if we’re already performing ahead of our own historical average, stretching further to the industry average may prove more difficult.
Step 4: Estimate the potential
Compared to production lines (in Theory of Constraints), there is significantly more uncertainty in the stages of our business process. This is because we don’t have complete control over the inputs – these are largely influenced by the market and our competitors.
Due to this, we have to predict which stage/s we can best influence to increase total throughput. Using our monthly averages, industry benchmarks and general business knowledge (as per our fictitious eCommerce business) we can estimate:
- how much improvement we think we could make in each stage;
- how much this would cost;
- how much lifetime value this would create; and
- and how long it would take.
Each of these forms a mini business case we can quickly assess.
Step 5: Rank the opportunities & Identify the Constraint
Based on the above, we’ve ranked our different improvement opportunities as follows below. We’ve chosen to rate them based on the combination of ROI & revenue velocity — you don’t have to do it this way but we’re equally interested in the speed at which we can increase monthly revenue as the total ROI (especially when we can make such dramatic increases in months).
Of course in a real-world scenario, this step would involve a lot more rigour, and in many cases (particularly for larger and more complex enterprises) we’d advocate running a number of innovation sprints to yield the highest quality options for each of these stages. For the purposes of demonstration, we’ve jumped straight to the conclusion!
We estimate (based on the above) the greatest business case is for our ability to convert people from browsers (clicks) into leads (Deliberation). In our case this means people adding products to their shopping cart. We believe we can move from 20% – 25% in 2 months with a concerted UX and communications program. This will cost $50,000 but will yield an additional $2.65M over the next 3 years. A huge 3,175% ROI (factoring a 60% margin) in a relatively short period of time.
Our next highest opportunity is in converting more of our new orders into long-standing customers. We estimate we could increase this 25% – 30% in 1 month with an on-boarding and up-sell communications program. This would yield an additional $2.12M over 3 years for an investment of $100,000. A reasonable 1,270% ROI (at 60% margin) — but not as significant as the previous opportunity.
Luck may have it we have the funding and capacity to focus on both, and in many organisations we’d recommend on running as many as three of these in parallel (but ideally no more!) For our fictitious shop let’s just focus on one.
Step 6: Elevate the Constraint — Rinse & Repeat!
Step 6 is the heart of The Exponential Method. Identify the area of your business that is most constraining your flow of value — elevate it — then find the next constraint and repeat the process!
The reason it’s called The Exponential Method is because doing this means you can continuously increase your flow of value until you’ve maximised all of your throughput for the current market… and then you can go back to the Design process and create new business models (and products & services) to serve other existing markets — or (even better) create new markets!
And since the rise of exponential technologies, the number of these new (potential) markets is virtually limitless (and will continue to increase over time, exponentially). So it is genuinely possible to have exponential growth into the future — but you must be willing to continually re-assess your business in this way and ACT. If you do not act you will not grow. You must be decisive — even if it means getting things wrong on occasion.
Here’s an example of how this would work in our fictitious eCommerce store.
That’s essentially 100% growth in 12 months. If we can achieve that every year then it looks something like the below — an exponential growth curve.
We’ve seen this kind of growth in many recent tech “unicorns”. What we’re suggesting is that using this approach (based on the Theory of Constraints) and a range of Digital Transformation Plays (see part 1) — you can harness a more systematic approach to realising this kind of growth for your business.