Instantly Improve The Bottom Line Impact Of Your Product Development Efforts — Michael Boumansour — Medium

Sound too good to be true? Perhaps, but in most cases what I am about to describe requires very little effort, time, investment, or significant change. The only change required is the criteria you use in making product development decisions. The criteria I am referring to is called Cost of Delay.

Cost of Delay is simply the cost associated with holding off on doing one thing to do another. Effectively time based opportunity cost. It allows you to understand the economic impact of time on your product development options. It is an objective approach that incorporates both value and urgency and reduces the amount of human guesswork involved with PD decision making.

Some typical questions CoD can help answer are:

  • Is our backlog prioritized in a way that gets us the most bang for the buck?
  • What is the bottom line impact of delaying our release a month?
  • Should we drop what we are going to go after a new opportunity that has just come up?
  • Can we justify investment in automated testing and deployment?
  • Have we reached a point on this project where we should kill it?

So let’s walk through a somewhat real world example of cost of delay and demonstrate how it can be used to answer some of the questions above. The table below represents a backlog of 10 items. For each item there is the potential benefit, the probability of that benefit, and the probable benefit. Benefit can be in the form of additional earnings, protected earnings, costs saved, and costs avoided. All benefit is on a per week basis. Lead time represents the time to go from planning to production. Cost of Delay is the sum of all probable benefit columns. CD3 is the Cost of Delay Divided by the Duration(Lead Time). We will discuss CD3 in more detail later. The backlog represents a total of 65 weeks of work.

A couple of notes regarding the example. First, this is a very straight forward example for illustrative purposes. Things like limited windows of opportunity, being late to market, regulatory compliance, etc. that can complicate the cost of delay are not part of this example. Second, I don’t discuss how the benefit of each backlog item is derived given that is one of the primary responsibilities of a product development organization. This same approach can be done in a relative manner if financial benefit cannot be obtained, but in that case I would ask if we haven’t identified financial benefit at least to some degree why are we considering these options in the first place?

Let’s go through a couple of the backlog items to illustrate. Backlog item 1 has potential added earnings of $10,000/week with a probability of 70% so the probable earnings added are $7000/week($10,000 * 0.7). There is no other benefit associated with this item so it’s cost of delay is $7000/week. Saying it another way every week that goes by without item 1 in production costs us $7000 in additional earnings. The lead time is 5 weeks so CD3 is $1,400($7000 / 5). Item 8 has $700 in probable earnings added and $600 in probable earnings protected so its cost of delay is $1,300/week. Its lead time is 4 weeks so CD3 is $325.

Ok so how can we now use this information to our benefit? Let’s first look at using it to help prioritize the backlog. I have seen companies prioritize their backlogs in countless ways ranging from hyper objective considering a dozen different variables to whatever the product owner is feeling like on any given day. We are going to look at 4 ways we could prioritize the backlog and compare the economic impact of each.

Batch Release

In the case of the batch release we are choosing to build all of the backlog items before releasing any of them. The order in which we build the items is irrelevant from an economic point of view because we are releasing them all at the same time. Since none of the items are released until all have been completed the total cost of delay will be the sum of all item’s cost of delay * 65 for a total of $3,445,650

Highest Value Item First

Next we will prioritize based on building and releasing the highest item first. We calculate the total cost of delay for each item with the following formula:

Lead time of priority item * Sum( Cost of Delay of remaining items) + total cost of delay of the previous priority item. For instance item 5 is the first priority with an individual cost of delay of $16,000/week. The total cost of delay is:

(22 * $53,010) = $1,166,220

Item 10 is the next priority so its total cost of delay is:

(7 * $37,010) + $1,166,220 = $1,425,290

And so on…

The total cost of delay will be $1,967,250.

Shortest Item First

Next we will prioritize based on building and releasing the shortest lead time item first. We calculate the cost of delay exactly as we did with the previous example. The total cost of delay is $1,966,430.

Highest CD3 Item First

Finally we will prioritize by building and releasing the item with the highest CD3 value first. Let’s take a minute to talk about CD3 and its benefit. CD3 is a way of weighting backlog items by cost of delay relative to the time it will take to deliver them. This is a form of Weighted Shortest Job First(WSJF). You could also use other criteria besides cost of delay for the weighing such as risk, customer satisfaction, etc. By prioritizing based on the CD3 score we are able to maximize the amount of value delivered over our 65 week time period. It provides a common mechanism for helping to decide on options that have different levels of value and urgency. People often conflate value and urgency, but they are in fact distinct. Something that is urgent isn’t necessarily valuable and vise versa. CD3 allows us to make objective decisions on trade-offs between a set of options removing a lot of the gut-feel, emotion, and politics that quite often go with product development decision making.

We calculate the total cost of delay just was we did the previous two examples. The total cost of delay is $1,725,680

Let’s review our four prioritization scenarios:

  • Batch Release - Cost of Delay = $3,445,650
  • Highest Value First - Cost of Delay =$1,967,250
  • Shortest Lead Time First - Cost of Delay = $1,966,430
  • Highest CD3 First - Cost of Delay= $1,725,680

By simply changing the order in which we build and deliver our backlog items using CD3 prioritization I have added between $241,540 and $1,719,970 of value to the bottom line with virtually no additional investment, change, or other disruptions to the teams or the business. That is the definition of low hanging fruit!

Let’s look at another way we can use this information to help us address a typical product development scenario. Suppose we have a product team who currently does their releases every quarter give or take. The team has been asking to build automated testing and a CI/CD pipeline that would allow them to release on demand. They have put together an estimate of 3 months and $500K in cost to build what they would need to achieve this capability. In addition the team feels the automation would improve their average lead time by conservatively by 20%. The PM has said she would love to do it, but we cannot justify the cost right now or delaying the business features that have been prioritized.

Let’s assume the team will do 4 batch releases over the next 65 weeks. They are prioritizing using CD3.

Their total cost of delay would be $1,883,850. But is the PM correct in that they cannot justify the investment in automation and delay the implementation of the business features? If the team were to take 3 months to build their required automation it would then allow them to release on demand and move away from the quarterly/periodic releases. That ability now brings their cost of delay of the features in the backlog down to the following:

In addition the automation will bring the team’s lead times down by an average of 20% which will further reduce the total cost of delay to the following:

So the investment in automation would reduce our total cost of delay by $503,006 and thus pay for itself in the same year! There would be some delay to the features in the backlog, but again from an economic point of view that is clearly justified.

Beyond using cost of delay as a decision making tool I believe what this demonstrates is just how critical it is to focus on lead time and continuously working to reduce it. Time truly is money! I hope this article has given you a taste of how valuable this kind of analysis can be in making product development decisions. I welcome and encourage any feedback you may have. My contact information is available on the Agile Creatives Website.



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