It's essential to regularly evaluate and address tech debt as it can
significantly impact a mature product's overall health and sustainability. If
left unaddressed, it can build up and require a massive focus from the team that
can disrupt existing customers or prevent you from adding new customers to the
product until addressed (this is something I've run into before, and it's no
fun!).
Here's how I approach it:
1. Regular technical reviews: I schedule regular technical reviews with my
development team to identify any technical debt that has accumulated and
determine the best way to address it. We typically have a staff-level
engineer or dedicated architect who can provide regular guidance and reviews
as we build to ensure we consider the larger technical vision and the scale
we need to deliver.
2. Budget for tech debt: I allocate a budget specifically for addressing tech
debt and ensure that it is included in our development plan. I use three
buckets at the team level to align what percentage of our overall capacity
to devote to each: Innovation (new features, new products), Iteration
(incremental enhancements), and Operation (tech debt, bug fixes, etc.).
3. Incorporate tech debt into prioritization: Once you have the target capacity
allocation across the big three buckets, you can incorporate tech debt into
the product backlog and prioritize it alongside new features and
enhancements. This helps ensure that you take a proactive approach to reduce
tech debt and improve the product's codebase.
In conclusion, considering tech debt is an ongoing process when working on a
mature product. By regularly evaluating and addressing it, you can ensure that
your product remains healthy, scalable, and sustainable over time.
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Managing Mature Products
1 answer
VP Product Management, Contentful | Formerly Twilio, SendGrid • February 2
1 answer
VP Product Management, Contentful | Formerly Twilio, SendGrid • February 1
I've found it helpful to craft a ~3-year product strategy that articulates the
market and trends, the challenges/opportunities, and the product's path forward
with coherent actions to address those challenges. This frames the product's
direction and how it will impact the company and customers you serve.
From there, determine the % allocation of your teams' capacity across investment
buckets. Agree with your team on how you'll spend your time across these to
achieve your product strategy:
1. Innovation: bold changes to make leaps and bounds towards the customer
journey vision. E.g., new features, the overhaul of existing features, and
integrations with partners.
2. Iteration: incremental changes to the existing product to deliver additional
customer & business value. E.g., conversion funnel optimizations, A/B
testing, and minor fixes that provide an incremental lift of a KPI.
3. Operation: The cost of managing a modern SaaS product. E.g., Security/data
privacy, performance/uptime, tech debt/upgrades, and bug fixes.
Next, you can consider the opportunities/ideas that may fall into each of these
buckets to create a stack rank for each based on the Impact it can have. Again,
a simple scoring framework can help, like RICE (detailed below). While
prioritizing within each bucket, consider the following:
1. Align with the product vision and goals: Ensure that the features being
considered align with the product's long-term vision and goals and that they
support growth initiatives. This is often the first filter when prioritizing
items. You can take additional steps to determine Impact and Effort if an
opportunity is aligned.
2. Evaluate customer needs and feedback: Regularly gather customer feedback and
analyze data to understand their needs and priorities. Is this opportunity
impactful to these customers by solving a significant problem? How many
customers might this opportunity affect?
3. Consider the cost-benefit of each feature: Evaluate the resources and time
required to develop and implement each feature and weigh that against the
potential benefits. A helpful framework for this is RICE, where R is the
Reach (# of customers), I is Impact (degree of Impact on these customers), C
is confidence (how much evidence have we gathered to support our
assumptions), E is the Effort (how much effort and time might it take to
develop this solution?). You take R*I*C divided by E to provide a numerical
score.
4. Balance short-term and long-term benefits: Consider the Impact of each
feature on both immediate and future product success.
5. Collaborate with cross-functional teams: Work closely with design,
engineering, and marketing teams to ensure that all relevant perspectives
are taken into account when making decisions.
1 answer
VP Product Management, Contentful | Formerly Twilio, SendGrid • February 1
Business objectives help the broader team and business understand if they've
achieved the intended impact but are difficult for a product team to use sprint
to sprint for a few reasons:
* Revenue isn't super actionable for the team: if it goes down or up, it's not
immediately obvious what actions the team should take in response.
* Business outcomes are often lagging metrics: length of sales cycles, churn,
and expansion all impact revenue, and this takes time. It doesn't enable the
team to take new actions in response to these sprint by sprint.
* A complete focus on financial metrics might cause unintended behavior: We've
all heard about the Wells Fargo example where they had a KR of selling eight
products to every customer, which led to teams signing up customers for
products without their knowledge. With business outcomes or financial metrics
as the only objectives given to product teams, they could be pulled into
short-term thinking to hit revenue growth instead of focusing on the customer
behaviors they need to change. With so much revenue not controlled by the
product team itself (sales cycle, pricing, discounting, renewals,
expansions), teams should be looking at sub-metrics that are more leading and
actionable.
To translate business objectives to product objectives, I'm a big fan of Josh
Seiden's book, Outcomes over Output as a helpful framing. In this book, he
defines an outcome as a change in customer behavior that drives business
results.
Using this framing, teams can ask these questions to find product objectives and
associated metrics:
* What are the user and customer behaviors that drive business results?
* How can we get people to do more of those behaviors?
* How do we know we're right?
1 answer
VP Product Management, Contentful | Formerly Twilio, SendGrid • January 4
The best PMs define success before building a feature. To define success, teams
should think through:
1. The customer problem they're solving, what does it look like when solved
(for the customer and the business)?
2. How impactful is it if solved (time-saving, cost-saving,
revenue-generating)?
3. How does solving this problem help the company achieve its longer-term
vision/strategy? Is there a KPI or measure for the feature that helps the
team know they're moving toward that strategy?
Once the feature is launched, there are a few different ways to determine
whether a new feature or update has been successful:
* Track usage metrics: such as the number of users using the feature, the
frequency with which they are using it, and any changes in retention or
engagement.
* Gather customer feedback: This can be done through surveys, user interviews,
or tracking social media mentions of the product.
* Monitor for changes in key performance indicators (KPIs): Depending on the
goals of the feature or update, you can also monitor for changes in relevant
KPIs, such as revenue, conversion rate, or customer satisfaction.
* A/B test: If you're unsure how a new feature or update will be received, you
can run an A/B test to compare the performance of the new feature or update
against a control group.
Lastly, a helpful question that Sean Ellis has popularized is the PMF test: ask
users, “how would you feel if you could no longer use the product?” and measure
the percentage who answer “very disappointed.” After benchmarking nearly a
hundred startups with his customer development survey, Ellis found that the
magic number was 40%. This can be a helpful tool to identify users to interview
further and segment your customer base around those customers that find a lot of
value in your product that you should be targeting.