AKF Partners

Abbott, Keeven & Fisher Partners Partners in Growth

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Engineering Metrics

April 3, 2017  |  Posted By: AKF

A topic that often results in great debate is “how to measure engineers?” I’m a pretty data driven guy so I’m a fan of metrics as long as they are 1) measured correctly 2) used properly and 3) not taken in isolation. I’ll touch on these issues with metrics later in the post, let’s first discuss a few possible metrics that you might consider using. Three of my favorite are: velocity, efficiency, and cost.

  • Velocity – This is a measurement that comes from the Agile development methodology. Velocity is the aggregate of story points (or any other unit of estimate that you use e.g. ideal days) that engineers on a team complete in a sprint. As we will discuss later, there is no standard good or bad for this metric and it is not intended to be used to compare one engineer to another. This metric should be used to help the engineer get better at estimating, that’s it. No pushing for more story points or comparing one team to another, just use it as feedback to the engineers and team so they can get more predictable in their work.
  • Efficiency – The amount of time a software developer spends doing development related activities (e.g. coding, designing, discussing with the product manager, etc) divided by their total time available (assume 8 – 10 hours per day) provides the Engineering Efficiency. This is a metric designed to see how much time software developers are actually spending on developing software. This metric often surprises people. Achieving 60% or more is exceptional. We often see dev groups below 40% efficiency. This metric is useful for identifying where else engineers are spending their time. Are there too many company meetings not directly related to getting products out the door? Are you doing too many HR training sessions, etc? This metric is really for the management team to then identify what is eating up the nondevelopment time and get rid of it.
  • Cost – Tech cost as a percentage of revenue is a good cost based metric to see how much you are spending on technology. This is very useful as it can be compared to other tech (SaaS or other webbased companies) and you can watch this metric change over time. Most startups begin with their total tech cost (engineers, hosting, etc) at well over 50% of revenue but this should quickly reduce as revenue grows and the business scales. Yes, scaling a business involves growing it cost effectively. Established companies with revenues in the tens of millions range usually have this percentage below 10%. Very large companies in the hundreds of millions in revenue often drive this down to 57%.

Now that we know about some of the most common metrics, how should they be used? The most common way managers and executives want to use metrics is to compare engineers to each other or compare a team over time. This works for the Efficiency and the Cost metrics, which by the way are primarily measurements of management effectiveness. Managers make most of the cost decisions including staffing, vendor contracts, etc. so they should be on the hook to improve these metrics. In terms of product out the door as measured by story points completed each sprint a.k.a. Velocity, as mentioned above, is to be used to improve estimates, not try to speed up developers. Using this metric incorrectly will just result in bloated estimates, not faster development.

An interesting comparison of developers comes from a 1967 article by Grant and Sackman in which they stated a ratio of 28:1 for the time required by the slowest versus the fastest programmer to complete a task. This has been a widely cited ratio but a paper from 2000 revised this number to 4:1 at the most and more likely 2:1. While a 2x difference in speed is still impressive it doesn’t optimize for the overall quality of the product. An engineer who is very fast and with high quality but doesn’t interact with the product managers isn’t necessarily the overall most effective. My point is that there are many other factors to be considered than just story points per release when comparing engineers.



April 3, 2017  |  Posted By: AKF

As a frequent technology writer I often find myself referring to the method or process that teams use to produce software. The two terms that are usually given for this are software development life cycle (SDLC) and product development life cycle (PDLC). The question that I have is are these really interchangeable? I don’t think so and here’s why.

Wikipedia, our collective intelligence, doesn’t have an entry for PDLC, but explains that the product life cycle has to do with the life of a product in the market and involves many professional disciplines. According to this definition the stages include market introduction, growth, mature, and saturation. This really isn’t the PDLC that I’m interested in. Under new product development (NDP) we find a defintion more akin to PDLC that includes the complete process of bringing a new product to market and includes the following steps: idea generation, idea screening, concept development, business analysis, beta testing, technical implementation, commercialization, and pricing.

Under SDLC, Wikipedia doesn’t let us down and explains it as a structure imposed on the development of software products. In the article are references to multiple different models including the classic waterfall as well as agile, RAD, and Scrum and others.

In my mind the PDLC is the overarching process of product development that includes the business units. The SDLC is the specific steps within the PDLC that are completed by the technical organization (product managers included). An image on HBSC’s site that doesn’t seem to have any accompanying explanation depicts this very well graphically.

Another way to explain the way I think of them is to me all professional software projects are products but not all product development includes software development.  See the Venn diagram below. The upfront (bus analysis, competitive analysis, etc) and back end work (infrastructure, support, depreciation, etc) are part of the PDLC and are essential to get the software project created in the SDLC out the door successfully.  There are non-software related products that still require a PDLC to develop.

Do you use them interchangeably?  What do you think the differences are?


Build v. Buy

April 3, 2017  |  Posted By: AKF

In many of our engagements, we find ourselves helping our clients understand when it’s appropriate to build and when they should buy.

If you perform a simple web search for “build v. buy” you will find hundreds of articles, process flows and decision trees on when to build and when to buy. Many of these are costcentric decisions including discounted cash flows for maintenance of internal development and others are focused on strategy. Some of the articles blend the two.

Here is a simple set of questions that we often ask our customers to help them with the build v. buy decision:

1. Does this “thing” (product / architectural component / function) create strategic differentiation in our business?

Here we are talking about whether you are creating switching costs, lowering barriers to exit, increasing barriers to entry, etc that would give you a competitive advantage relative to your competition. See Porter’s Five Forces for more information about this topic. If the answer to this question is “No – it does not create competitive differentiation” then 99% of the time you should just stop there and attempt to find a packaged product, open source solution, or outsourcing vendor to build what you need. If the answer is “Yes”, proceed to question 2.

2. Are we the best company to create this “thing”?

This question helps inform whether you can effectively build it and achieve the value you need. This is a “core v. context” question; it asks both whether your business model supports building the item in question and also if you have the appropriate skills to build it better than anyone else. For instance, if you are a social networking site, you *probably* don’t have any business building relational databases for your own use. Go to question number (3) if you can answer “Yes” to this question and stop here and find an outside solution if the answer is “No”. And please, don’t fool yourselves – if you answer “Yes” because you believe you have the smartest people in the world (and you may), do you really need to dilute their efforts by focusing on more than just the things that will guarantee your success?

3. Are there few or no competing products to this “thing” that you want to create?

We know the question is awkwardly worded – but the intent is to be able to exit these four questions by answering “yes” everywhere in order to get to a “build” decision. If there are many providers of the “thing” to be created, it is a potential indication that the space might become a commodity. Commodity products differ little in feature sets over time and ultimately compete on price which in turn also lowers over time. As a result, a “build” decision today will look bad tomorrow as features converge and pricing declines. If you answer “Yes” (i.e. “Yes, there are few or no competing products”), proceed to question (4).

4. Can we build this “thing” cost effectively?

Is it cheaper to build than buy when considering the total lifecycle (implementation through endoflife)
of the “thing” in question? Many companies use cost as a justification, but all too often they miss the key points of how much it costs to maintain a proprietary “thing”, “widget”, “function”, etc. If your business REALLY grows and is extremely successful, do you really want to be continuing to support internally developed load balancers, databases, etc. through the life of your product? Don’t fool yourself into answering this affirmatively just because you want to work on something neat. Your job is to create shareholder value – not work on “neat things” – unless your “neat thing” creates shareholder value.

There are many more complex questions that can be asked and may justify the building rather than purchasing of your “thing”, but we feel these four questions are sufficient for most cases.

A “build” decision is indicated when the answers to all 4 questions are “Yes”.

We suggest seriously considering buying or outsourcing (with appropriate contractual protection when intellectual property is a
concern) anytime you answer “No” to any question above.