Are your maintenance cycles killing your budget?
Teams have long relied on experience and gut feeling when determining what needs to be fixed, optimized or left alone in software.
But what happens when there’s a better way?
Data-backed decision making is revolutionizing software maintenance by…
- Highlighting important issues before they become problems
- Prioritizing tasks based on user behavior, not assumptions
- Eliminating wasted spending on low-value fixes
Teams can optimize their maintenance workflows when they make decisions based on…
Wait… what?
You’ll Learn
- How Much Software Maintenance Really Costs
- Why Guessing Isn’t Cutting It Anymore
- Why and How to Use Data-Backed Decisions
- Software Maintenance isn’t what it used to be
- Stop guessing. Start making data-backed decisions today
How Much Software Maintenance Really Costs
According to industry research, software maintenance can account for 15-25% of the yearly development budget.
That means if a team spends $500,000 to build a system they can expect to spend over $1 million maintaining it throughout its lifetime.
Gartner also estimates that between 55-80% of companies spend their IT budgets on maintaining existing software versus developing new software.
That is a tremendous amount of money going towards just keeping existing systems running.
Maintenance isn’t the issue. All software requires maintenance.
The problem is that all too often teams have no idea where problems actually lie.
When teams aren’t armed with data they tend to allocate money towards “guessing” where maintenance is required.
Why Guessing Isn’t Cutting It Anymore
Let’s be honest…
Software maintenance is largely driven by opinion.
Sure there are bug reports. And support teams do their best to communicate issues as they see them. But when it comes down to prioritizing maintenance teams often spend too much time…
- Pulling meetings to discuss where maintenance is needed
- Running meetings where no decision can be agreed upon
- Fixing problems that don’t truly impact the user experience
All while running out of time (and money) to actually fix the things that do matter.
Maintenance via guessing looks a lot like this…
- Scraping by with expensive, makeshift solutions that fail to address the root problem.
- Putting out fires instead of implementing preventative maintenance.
- Everyone going in a slightly different direction because “no one knows best.”
If any of that sounds familiar then it may be time for a change of pace.
Why and How to Use Data-Backed Decisions
Welcome data-backed decision making.
Instead of arguing about where maintenance is needed, teams can utilize real user data to identify issues before they become severe. Tools that allow teams to focus on continuous product design (like Quantum Metric) enable development teams to see how users actually interact with their software.
Why does this matter?
When there is data showing where users are struggling, which features have the highest friction, and what bugs are causing problems… maintenance becomes less about responding to issues and more about improving the product.
Data can help teams…
- Focus on fixing high-impact problems first. Instead of guessing which issues need priority, user data will show what’s hurting users (and the bottom line) the most.
- Reduce cost of maintenance. By devoting more time to what truly matters, teams spend less time debugging obscure issues that don’t provide value to users. Less time spent debugging equals more money in the budget for things that DO add value.
- Continually increase product quality. Each maintenance cycle is an opportunity to make the product better. When teams know what users need through their own behavior, they can make impactful changes that keep users happy.
One more thing about data…
Teams that have embraced using data to make decisions report being able to make decisions up to 5x faster than teams that don’t use data.
Research shows that companies with a strong data culture make decisions 5x faster than companies with weak or no culture of using data.
Data doesn’t just save money. It saves time.
Software Maintenance isn’t what it used to be
Here’s a wild thought…
What if software maintenance and product design were deeply intertwined?
Instead of developing software, shipping it and then transferring it to “maintenance,” what if the team was continuing to design and improve the product every single day?
When teams take a product-centric approach to software maintenance they’ll realize…
- Bug reports are opportunities to learn more about the product.
- Every performance issue is a chance to make the product faster.
- Every user session is a story about what the software can do next.
By merging the concepts of maintenance and product design teams can ensure they are building better software while spending less time (and money) maintaining it.
Stop guessing. Start making data-backed decisions today!
Making the switch to data-backed software maintenance is easier than most teams think.
Here are 4 steps to start building a data-driven maintenance process today.
1. Start by analyzing user behavior
At the core of every data-backed maintenance process is user behavior. Teams should begin by tracking user sessions, errors and feature usage. Once there is a general understanding of how users are interacting with the software the team will know where to focus efforts.
2. Triage issues by level of impact
Understanding impact is critical to the maintenance process. Some bugs impact few users while others can stop critical user flows. By identifying which bugs have the biggest impact on users teams can reduce time spent dealing with low value bugs.
3. Create a feedback loop with the data
Data should always be feeding back into the development process. By creating a centralized dashboard for the team to see real user data, everyone stays on the same page about what matters most.
4. Measure how data is impacting KPIs
Don’t forget to measure how maintenance is impacting KPIs. Are support tickets being reduced? Is user satisfaction increasing? Is less time and money being spent on maintenance? By measuring the team’s progress it becomes clear where to focus next.
Maintenance Made Simple
It’s time to retire the old way of doing maintenance.
Thanks to the rise of analytics tools teams can finally understand where their users are struggling within applications. By collecting data about user behavior after release teams can…
- Eliminate waste by only focusing on issues that impact users.
- Improve the overall quality of software by taking every opportunity to learn more about the product.
- Stop wasting time arguing about what to fix next. Data removes opinions and emotions from the equation.
Software maintenance doesn’t have to be expensive. Nor does it have to be a chore.
When teams start making data-backed decisions they’ll improve software faster than ever before.
Long live data-backed maintenance.