The Fundamental Reason Why You Fail to Deliver on Time (Plus the 3-Step Product Management Guide to Meeting Your Commitments)
Businesses across the globe fail to deliver on time. In the early days of prison warfare, a deadline meant a line that was drawn around a prison to deter prisoners from crossing. If they did, they’d be shot dead on sight! Nowadays, although you won’t get shot if you run over a deadline, it might still have a severe impact on your business.
In fact, 4 of the top 6 challenges faced by companies, as outlined in the 2020 MHI Annual Industry Report relate to faster delivery and higher customer expectations, including customer demands for lower costs (51%), customer demands on response times (48%), rising customer service expectations (47%), and customer demands for customization (41%).
In times of a saturated market and fierce competition, it’s critical to meet these expectations and deliver on your commitments. So, if you’re still trying to get on top of overdue tasks, it’s worth taking a step back and analyzing the root cause of failing to deliver on time.
The Main Cause of Failing to Deliver on Time
Тhe most common reason behind failing to meet your commitments and deliver on time is setting unrealistic expectations.
A case study conducted by Calleam Consulting demonstrates how inaccurate estimates led to the significant delay of the completion of the Baggage Handling System of Denver International Airport during the 1990s. The unreliable predictions were off by 16 months, a delay which cost the city of Denver an eye-watering $560 million. Just two decades later, the system has been decommissioned.
This is just one of the many projects that failed due to unrealistic deadlines.
The Sydney Opera House was supposed to be completed in 1963, for $7 million. A scaled-back version opened ten years later, in 1973, with a final price tag of $102 million.
Managers fall victim to our inbuilt tendency to underestimate how long it takes to complete our work. And how can we possibly predict our exact delivery times with the unpredictability of knowledge work? Are we actually capable of foreseeing the exact time that a feature will take to go through the whole process while handling the rest of our work in progress at the same time? Do we know for sure that there won’t be any additional work coming in between, any dependencies, defects, bottlenecks, or external blockers that might cause a delay?
The problem is rooted in the expectation of answering our customers with a single certain delivery date. Yet, that tends to be the norm in practice. It seems that we’d rather come up with a single certain commitment that ends up being wrong than express any uncertainty.People feel more comfortable being wrong than uncertain. Click To Tweet
Pursuing super-ambitious goals may have a far-reaching negative impact on your employees as well. Here are just a few of the ramifications that come with it:
- Burnout & low-quality results. If the expectations placed on your employees are too high, they will be forced to work harder to catch up and their performance will eventually tank. If they’re in the throes of full-fledged burnout, your employees will no longer be able to work efficiently, and their work will be less than stellar. They will rush tasks and cut corners, which will cause mistakes and lead to poor-quality outcomes.
- Missed delivery dates. Impossible deadlines mean it’s unlikely that your team will be able to achieve them, and so they will often miss targets. If they regularly fail to deliver on time, the question on the table will be “Why is your team underachieving?” while they have been forced to push themselves to their limits to meet unrealistic expectations.
- Low morale. Meeting a deadline is a motivation booster. However, if your team constantly misses their deadlines, your entire team can feel like they’re not achieving. Your employees need to know how their work brings value to your company. They need to see how their efforts contribute to business success. If they don’t, this can impact their self-esteem, motivation, and engagement, which would damage your company’s bottom-line.
- Higher staff turnover. Voluntary turnover is a problem that’s costing the US economy $1 Trillion per year, according to Gallup. And this problem is self-inflicted by organizations. If staff feel like they can never and will never be able to meet your expectations, they may realize their only option is to resign. Not only do you lose up to two times their annual salary in turnover costs, but all their expertise and knowledge of your company walk away through the front door too.
Setting realistic expectations and meeting customer’s requirements have to be a priority for every business. Let’s explore the steps you can take to achieving more predictable results without overburdening your workforce.
The 3-Step Product Management Guide to Meeting Your Commitments
To be able to deliver on your customers’ expectations, you should set and manage realistic goals in the first place. Here is our 3-step product management guide on how to meet your commitments and achieve a more predictable delivery workflow.
1. Stop Estimating and Start Forecasting
Knowledge work is notorious for its unpredictable nature. Making accurate future predictions allows organizations to define service level agreements with more confidence and deliver value to their customers on time, in a consistent, predictable manner.
One of the most pressing questions every manager faces is “When will this be done?”. And it might be a challenging question if you don’t have the means to give a confident answer.
Leader of the Kanban movement
"We spend too much energy speculating about the future, rather than studying the recent past and using factual data. We are too ready to believe that our newest work is unique and different when in truth it is much more similar to work we do regularly than we care to admit."
When trying to provide the answer to the “When will this be done” question, there are two approaches you can take – an estimate and a forecast. What’s the difference?
Estimates are predictions based on intuition, guesswork, or judgment. The prediction is communicated as a single value, and it doesn’t involve any probability of its occurrence.
Forecasts, on the other hand, are based on past performance data. The prediction is delivered as a range of values and the probability of those values occurring.Forecasting is faster, cheaper, and more reliable than estimating. Click To Tweet
The Cycle Time Scatterplot can be of great help when it comes to making probabilistic forecasts for a work item. This diagram represents your historical performance data, displaying all of your completed tasks as dots scattered on a plot.
The dotted horizontal lines stretching across the graph are called percentile lines. We use percentiles to define the probability of different commitments being met.
For example, the 85th percentile on our scatterplot points to 10 days. This means that 85% of the tasks so far have been completed in less than 10 days. We can now say that any future task we take on has an 85% chance of being finished in less than 10 days. We can also say with 95% certainty that we can deliver any new work within 13 days.
You can also filter your data by classes of service. Using Classes of service (CoS) is an approach to prioritizing your work effectively. It is highly likely that the 85th percentile for Standard CoS comes with a different cycle time than the 85th percentile for Expedites. That way, you can provide different Service Level Agreements (SLA) for different work items you’re committing to. You can do the same by filtering your data using types of work items like Stories, Tasks, or Bugs. The results will still be valid.
Of course, the percentile you use to define SLAs largely depends on your context. You and your clients may be comfortable settling for an 85% level of certainty, or, you may both need a confidence level that’s higher than that.
The Cycle Time Scatterplot provides a range of commitments, along with a probability of each commitment happening, by using your past performance data. Probabilistic forecasting is amongst the most effective methods for predicting delivery times with maximum accuracy.
Meet the Author
Sonya Siderova is a passionate product manager and a driving force behind Nave, a Kanban analytics suite that helps teams become more efficient through data-driven decision making. When she's not catering to her two little ones, you might find Sonya absorbed in a good heavyweight boxing match or behind a screen crafting a new blog post.
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