Modern product development is witnessing a drastic shift. Disruptive ideas and ambiguous business conditions have changed the way products are developed. Product development is no longer guided by existing processes or predefined frameworks. Delivering on time is a baseline metric, as is software quality. Today, businesses are competing to innovate. They are willing to invest in groundbreaking products with cutting-edge technology. Cost is no longer the constraint—execution is.
Can product managers then continue to rely upon processes and practices aimed at traditional ways of product building? How do we ensure that software product builders look at the bigger picture and do not tie themselves to engineering practices and technology viability alone? Understanding the business and customer context is essential for creating valuable products. In this article, we are going to identify what success means to us in terms of product development.
This article is an excerpt from the book Lean Product Management written by Mangalam Nandakumar.
For the kind of impact that we predict our feature idea to have on the Key Business Outcomes, how do we ensure that every aspect of our business is aligned to enable that success? We may also need to make technical trade-offs to ensure that all effort on building the product is geared toward creating a satisfying end-to-end product experience.
When individual business functions take trade-off decisions in silo, we could end up creating a broken product experience or improvising the product experience where no improvement is required. For a business to be able to align on trade-offs that may need to be made on technology, it is important to communicate what is possible within business constraints and also what is not achievable. It is not necessary for the business to know or understand the specific best practices, coding practices, design patterns, and so on, that product engineering may apply. However, the business needs to know the value or the lack of value realization, of any investment that is made in terms of costs, effort, resources, and so on.
The section addresses the following topics:
The need to have a shared view of what success means for a feature idea
Defining the right kind of success criteria
Creating a shared understanding of technical success criteria
"If you want to go quickly, go alone. If you want to go far, go together. We have to go far — quickly."
Al Gore
Planning for success doesn't come naturally to many of us. Come to think of it, our heroes are always the people who averted failure or pulled us out of a crisis. We perceive success as 'not failing,' but when we set clear goals, failures don't seem that important. We can learn a thing or two about planning for success by observing how babies learn to walk. The trigger for walking starts with babies getting attracted to, say, some object or person that catches their fancy. They decide to act on the trigger, focusing their full attention on the goal of reaching what caught their fancy. They stumble, fall, and hurt themselves, but they will keep going after the goal. Their goal is not about walking. Walking is a means to reaching the shiny object or the person calling to them. So, they don't really see walking without falling as a measure of success. Of course, the really smart babies know to wail their way to getting the said shiny thing without lifting a toe.
Somewhere along the way, software development seems to have forgotten about shiny objects, and instead focused on how to walk without falling. In a way, this has led to an obsession with following processes without applying them to the context and writing perfect code, while disdaining and undervaluing supporting business practices. Although technology is a great enabler, it is not the end in itself. When applied in the context of running a business or creating social impact, technology cannot afford to operate as an isolated function. This is not to say that technologists don't care about impact. Of course, we do.
Technologists show a real passion for solving customer problems. They want their code to change lives, create impact, and add value. However, many technologists underestimate the importance of supporting business functions in delivering value. I have come across many developers who don't appreciate the value of marketing, sales, or support. In many cases, like the developer who spent a year perfecting his code without acquiring a single customer, they believe that beautiful code that solves the right problem is enough to make a business succeed. Nothing can be further from the truth
Most of this type of thinking is the result of treating technology as an isolated function. There is a significant gap that exists between nontechnical folks and software engineers. On the one hand, nontechnical folks don't understand the possibilities, costs, and limitations of software technology. On the other hand, technologists don't value the need for supporting functions and communicate very little about the possibilities and limitations of technology. This expectation mismatch often leads to unrealistic goals and a widening gap between technology teams and the supporting functions. The result of this widening gap is often cracks opening in the end-to-end product experience for the customer, thereby resulting in a loss of business. Bridging this gap of expectation mismatch requires that technical teams and business functions communicate in the same language, but first they must communicate.
Setting SMART goals for team
In order to set the right expectations for outcomes, we need the collective wisdom of the entire team. We need to define and agree upon what success means for each feature and to each business function. This will enable teams to set up the entire product experience for success. Setting specific, measurable, achievable, realistic, and time-bound (SMART) metrics can resolve this.
We cannot decouple our success criteria from the impact scores we arrived at earlier. So, let's refer to the following table for the ArtGalore digital art gallery:
The estimated impact rating was an indication of how much impact the business expected a feature idea to have on the Key Business Outcomes. If you recall, we rated this on a scale of 0 to 10. When the estimated impact of a Key Business Outcomes is less than five, then the success criteria for that feature is likely to be less ambitious. For example, the estimated impact of "existing buyers can enter a lucky draw to meet an artist of the month" toward generating revenue is zero. What this means is that we don't expect this feature idea to bring in any revenue for us or put in another way, revenue is not the measure of success for this feature idea. If any success criteria for generating revenue does come up for this feature idea, then there is a clear mismatch in terms of how we have prioritized the feature itself.
For any feature idea with an estimated impact of five or above, we need to get very specific about how to define and measure success. For instance, the feature idea "existing buyers can enter a lucky draw to meet an artist of the month" has an estimated impact rating of six towards engagement. This means that we expect an increase in engagement as a measure of success for this feature idea. Then, we need to define what "increase in engagement" means. My idea of "increase in engagement" can be very different from your idea of "increase in engagement." This is where being S.M.A.R.T. about our definition of success can be useful.
Success metrics are akin to user story acceptance criteria. Acceptance criteria define what conditions must be fulfilled by the software in order for us to sign off on the success of the user story. Acceptance criteria usually revolve around use cases and acceptable functional flows. Similarly, success criteria for feature ideas must define what indicators can tell us that the feature is delivering the expected impact on the KBO. Acceptance criteria also sometimes deal with NFRs (nonfunctional requirements). NFRs include performance, security, and reliability.
In many instances, nonfunctional requirements are treated as independent user stories. I also have seen many teams struggle with expressing the need for nonfunctional requirements from a customer's perspective. In the early days of writing user stories, the tendency for myself and most of my colleagues was to write NFRs from a system/application point of view. We would say, "this report must load in 20 seconds," or "in the event of a network failure, partial data must not be saved." These functional specifications didn't tell us how/why they were important for an end user. Writing user stories forces us to think about the user's perspective. For example, in my team we used to have interesting conversations about why a report needed to load within 20 seconds. This compelled us to think about how the user interacted with our software.
It is not uncommon for visionary founders to throw out very ambitious goals for success. Having ambitious goals can have a positive impact in motivating teams to outperform. However, throwing lofty targets around, without having a plan for success, can be counter-productive. For instance, it's rather ambitious to say, "Our newsletter must be the first to publish artworks by all the popular artists in the country," or that "Our newsletter must become the benchmark for art curation." These are really inspiring words, but can mean nothing if we don't have a plan to get there.
The general rule of thumb for this part of product experience planning is that when we aim for an ambitious goal, we also sign up to making it happen. Defining success must be a collaborative exercise carried out by all stakeholders. This is the playing field for deciding where we can stretch our goals, and for everyone to agree on what we're signing up to, in order to set the product experience up for success.
Defining key success metrics
For every feature idea we came up with, we can create feature cards that look like the following sample. This card indicates three aspects about what success means for this feature. We are asking these questions: what are we validating? When do we validate this? What Key Business Outcomes does it help us to validate?
The criteria for success demonstrates what the business anticipates as being a tangible outcome from a feature. It also demonstrates which business functions will support, own, and drive the execution of the feature. That's it! We've nailed it, right? Wrong.
Success metrics must be SMART, but how specific is the specific? The preceding success metric indicates that 80% of those who sign up for the monthly art catalog will enquire about at least one artwork. Now, 80% could mean 80 people, 800 people, or 8000 people, depending on whether we get 100 sign-ups, 1000, or 10,000, respectively!
We have defined what external (customer/market) metrics to look for, but we have not defined whether we can realistically achieve this goal, given our resources and capabilities. The question we need to ask is: are we (as a business) equipped to handle 8000 enquiries? Do we have the expertise, resources, and people to manage this? If we don't plan in advance and assign ownership, our goals can lead to a gap in the product experience. When we clarify this explicitly, each business function could make assumptions.
When we say 80% of folks will enquire about one artwork, the sales team is thinking that around 50 people will enquire. This is what the sales team at ArtGalore is probably equipped to handle. However, marketing is aiming for 750 people and the developers are planning for 1000 people. So, even if we can attract 1000 enquiries, sales can handle only 50 enquiries a month! If this is what we're equipped for today, then building anything more could be wasteful. We need to think about how we can ramp up the sales team to handle more requests. The idea of drilling into success metrics is to gauge whether we're equipped to handle our success. So, maybe our success metric should be that we expect to get about 100 sign-ups in the first three months and between 40-70 folks enquiring about artworks after they sign up. Alternatively, we can find a smart way to enable sales to handle higher sales volumes.
Before we write up success metrics, we should be asking a whole truckload of questions that determine the before-and-after of the feature.
We need to ask the following questions:
What will the monthly catalog showcase?
How many curated art items will be showcased each month?
What is the nature of the content that we should showcase? Just good high-quality images and text, or is there something more?
Who will put together the catalog?
How long must this person/team(s) spend to create this catalog?
Where will we source the art for curation?
Is there a specific date each month when the newsletter needs to go out?
Why do we think 80% of those who sign up will enquire? Is it because of the exclusive nature of art? Is it because of the quality of presentation? Is it because of the timing? What's so special about our catalog?
Who handles the incoming enquiries? Is there a number to call or is it via email?
How long would we take to respond to enquiries?
If we get 10,000 sign-ups and receive 8000 enquiries, are we equipped to handle these? Are these numbers too high? Can we still meet our response time if we hit those numbers?
Would we still be happy if we got only 50% of folks who sign up enquiring? What if it's 30%? When would we throw away the idea of the catalog?
This is where the meat of feature success starts taking shape. We need a plan to uncover underlying assumptions and set ourselves up for success. It's very easy for folks to put out ambitious metrics without understanding the before-and-after of the work involved in meeting that metric. The intent of a strategy should be to set teams up for success, not for failure.
Often, ambitious goals are set without considering whether they are realistic and achievable or not. This is so detrimental that teams eventually resort to manipulating the metrics or misrepresenting them, playing the blame game, or hiding information. Sometimes teams try to meet these metrics by deprioritizing other stuff. Eventually, team morale, productivity, and delivery take a hit. Ambitious goals, without the required capacity, capability, and resources to deliver, are useless.
Technology to be in line with business outcomes
Every business function needs to align toward the Key Business Outcomes and conform to the constraints under which the business operates. In our example here, the deadline is for the business to launch this feature idea before the Big Art show. So, meeting timelines is already a necessary measure of success.
The other indicators of product technology measures could be quality, usability, response times, latency, reliability, data privacy, security, and so on. These are traditionally clubbed under NFRs (nonfunctional requirements). They are indicators of how the system has been designed or how the system operates, and are not really about user behavior. There is no aspect of a product that is nonfunctional or without a bearing on business outcomes. In that sense, nonfunctional requirements are a misnomer. NFRs are really technical success criteria. They are also a business stakeholder's decision, based on what outcomes the business wants to pursue.
In many time and budget-bound software projects, technical success criteria trade-offs happen without understanding the business context or thinking about the end-to-end product experience.
Let's take an example: our app's performance may be okay when handling 100 users, but it could take a hit when we get to 10,000 users. By then, the business has moved on to other priorities and the product isn't ready to make the leap.
This depends on how each team can communicate the impact of doing or not doing something today in terms of a cost tomorrow. What that means is that engineering may be able to create software that can scale to 5000 users with minimal effort, but in order to scale to 500,000 users, there's a different level of magnitude required.
There is a different approach needed when building solutions for meeting short-term benefits, compared to how we might build systems for long-term benefits. It is not possible to generalize and make a case that just because we build an application quickly, that it is likely to be full of defects or that it won't be secure. By contrast, just because we build a lot of robustness into an application, this does not mean that it will make the product sell better. There is a cost to building something, and there is also a cost to not building something and a cost to a rework. The cost will be justified based on the benefits we can reap, but it is important for product technology and business stakeholders to align on the loss or gain in terms of the end-to-end product experience because of the technical approach we are taking today.
In order to arrive at these decisions, the business does not really need to understand design patterns, coding practices, or the nuanced technology details. They need to know the viability to meet business outcomes. This viability is based on technology possibilities, constraints, effort, skills needed, resources (hardware and software), time, and other prerequisites. What we can expect and what we cannot expect must both be agreed upon. In every scope-related discussion, I have seen that there are better insights and conversations when we highlight what the business/customer does not get from this product release. When we only highlight what value they will get, the discussions tend to go toward improvising on that value. When the business realizes what it doesn't get, the discussions lean toward improvising the end-to-end product experience.
Should a business care that we wrote unit tests? Does the business care what design patterns we used or what language or software we used? We can have general guidelines for healthy and effective ways to follow best practices within our lines of work, but best practices don't define us, outcomes do.
To summarize we learned before commencing on the development of any feature idea, there must be a consensus on what outcomes we are seeking to achieve. The success metrics should be our guideline for finding the smartest way to implement a feature.
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