agile. Scoring it as 5 means the team expects the feature to significantly increase completion rate because customers will spend less time filling out forms. For a new dashboard color scheme feature, the team scores loan application completion rate impact as 0. Scoring it as 0 means the team expects the feature to have no impact on completion rate. (48/89)
Step two is score each feature on time to loan approval impact. The team scores each feature on a scale of 0 to 5. For the loan application auto-fill feature, the team scores time to loan approval impact as 3. Scoring it as 3 means the team expects the feature to moderately reduce time to approval because applications will be submitted faster. For the new dashboard color scheme feature, the team scores time to loan approval impact as 0. (49/89)
Step three is score each feature on customer financial health score impact. The team scores each feature on a scale of 0 to 5. For the loan application auto-fill feature, the team scores customer financial health score impact as 2. Scoring it as 2 means the team expects the feature to slightly improve financial health because customers who get loans faster can manage their finances better (50/89)
. For the new dashboard color scheme feature, the team scores customer financial health score impact as 0. (51/89)
Step four is score each feature on customer retention rate impact. The team scores each feature on a scale of 0 to 5. For the loan application auto-fill feature, the team scores customer retention rate impact as 4. Scoring it as 4 means the team expects the feature to significantly increase retention because customers who complete loan applications are more likely to stay. For the new dashboard color scheme feature, the team scores customer retention rate impact as 1 (52/89)
. Scoring it as 1 means the team expects the feature to slightly improve retention because customers might find the new colors more appealing. (53/89)
The team adds the four scores together. Adding the four scores means the team totals. The total score ranges from 0 to 20. The loan application auto-fill feature scores 14 (5 plus 3 plus 2 plus 4). The new dashboard color scheme feature scores 1 (0 plus 0 plus 0 plus 1). The team prioritizes features with the highest total scores. Prioritizing features with the highest total scores means the team focuses (54/89)
. The loan application auto-fill feature is prioritized over the new dashboard color scheme feature. Prioritizing the auto-fill feature means the team builds what matters. (55/89)
Last year, the 29-person DSDM team used the outcome-driven prioritization system for six months across 53 features in the backlog. Before the system, the team prioritized based on stakeholder pressure. Prioritizing based on stakeholder pressure meant the team built whatever the loudest stakeholder wanted. The team built a new dashboard color scheme feature because the marketing team insisted. Building the color scheme feature meant the team prioritized based on pressure (56/89)
. The color scheme feature took two weeks to build. Taking two weeks meant the team spent time. The color scheme feature had zero impact on loan application completion rate, time to loan approval, and customer financial health score. Having zero impact on three of four metrics meant the team wasted two weeks. (57/89)
After the system, the team prioritized based on customer outcomes. Prioritizing based on customer outcomes meant the team scored. The team scored 53 features. Scoring 53 features meant the team prioritized. The team built the top ten scoring features. Building the top ten scoring features meant the team focused. The top ten features had an average score of 13.2. Building these ten features meant the team built what mattered (58/89)
. These ten features increased the loan application completion rate from 31% to 52%. Increasing from 31% to 52% meant fewer applications were abandoned. These ten features decreased the time to loan approval from 11 days to 6 days. Decreasing from 11 days to 6 days meant customers waited less. These ten features improved the customer financial health score increase from 2 points to 6 points. Improving from 2 points to 6 points meant customers improved their finances (59/89)
. These ten features increased the customer retention rate from 63% to 71%. Increasing from 63% to 71% meant fewer customers left. Building these ten features meant the company saved $1,200,000 in annual loan revenue. (60/89)
For a DSDM team of 16 to 50, the outcome-driven prioritization system should have four steps. The system should score each feature on all four customer outcome metrics. The system should be applied to every feature in the backlog. For DSDM, the system should be part of the team's feasibility and foundations practice. The system is a prioritization tool. (61/89)
4. When You Make Good Decisions You Keep Customers by creating an outcome metric review cadence that reviews the four customer outcome metrics at the end of every DSDM timebox and decides whether to continue, pivot, or stop based on whether the metrics are trending toward their targets so that the team stops assuming that shipped features improve customer outcomes and starts verifying that shipped features improve customer outcomes. (62/89)
Walton kept customers at Walmart. When Walton kept customers, he created review cadences. When he created review cadences, he reviewed what mattered. When he reviewed what mattered, he kept customers. When he kept customers, he won. (63/89)
You should keep customers by creating an outcome metric review cadence that reviews the four customer outcome metrics at the end of every DSDM timebox and decides whether to continue, pivot, or stop based on whether the metrics are trending toward their targets. This way, the team stops assuming that shipped features improve customer outcomes and starts verifying that shipped features improve customer outcomes. (64/89)
For a finance services multinational, the outcome metric review cadence might look like this. The 29-person DSDM team creates an outcome metric review cadence. Creating the cadence means the team reviews what matters. Reviewing what matters means the team keeps customers. Keeping customers means the team wins.
The cadence has four steps. (65/89)
Step one is review the four metrics at the end of every timebox. The team reviews the four customer outcome metrics at the end of every DSDM timebox. The team reviews the current value of each metric. The team compares the current value to the target. The team compares the current value to the value at the start of the timebox. Comparing to the start value means the team reviews the trend. (66/89)
Step two is assess the trend. The team assesses whether each metric is trending toward its target. If the metric is trending toward the target, the team continues. If the metric is flat or trending away from the target, the team pivots. (67/89)
Step three is decide continue, pivot, or stop. The team makes a continue, pivot, or stop decision for each metric. For loan application completion rate, the metric increased from 31% to 52% over six months. The metric is improving. The team continues. For time to loan approval, the metric decreased from 11 days to 6 days over six months. The metric is improving. The team continues (68/89)
. For customer financial health score, the score increase improved from 2 points to 6 points over six months. The metric is improving. The team continues. For customer retention rate, the metric increased from 63% to 71% over six months. The metric is improving. The team continues.
Step four is document the decision. The team documents the continue, pivot, or stop decision for each metric. The team documents the reason for the decision. The team documents the next steps. (69/89)
The outcome metric review cadence happens at the end of every DSDM timebox. Happening at the end of every timebox means the team reviews regularly. Reviewing regularly means the team keeps customers. (70/89)
Last year, the 29-person DSDM team used the outcome metric review cadence for six months across six timebox reviews. Before the cadence, the team assumed that shipped features improved customer outcomes. Assuming shipped features improved customer outcomes meant the team did not verify. The team shipped features and assumed they worked. Shipping features and assuming they worked meant the team did not measure impact. The team shipped 41 features (71/89)
. Shipping 41 features meant the team delivered. But the loan application completion rate was 31%. That meant the team did not verify. (72/89)
After the cadence, the team verified that shipped features improve customer outcomes. Verifying that shipped features improve customer outcomes meant the team measured impact. The team reviewed six times. Reviewing six times meant the team verified each timebox. The team shipped 41 features over six months. Shipping 41 features meant the team delivered. The team measured the impact of each feature on the four customer outcome metrics. Measuring the impact meant the team verified (73/89)
. The team found that 26 of the 41 features improved at least one customer outcome metric. Finding that 26 of 41 features improved at least one metric meant the team verified. The team found that 15 of the 41 features had no impact on any customer outcome metric. Finding that 15 of 41 features had no impact meant the team pivoted. The team stopped building features that had no impact. Stopping building no-impact features meant the team saved time (74/89)
. The team focused on features that improved customer outcomes. Focusing on features that improved customer outcomes meant the team kept customers. Keeping customers meant the company saved $1,200,000 in annual loan revenue. (75/89)
For a DSDM team of 16 to 50, the outcome metric review cadence should have four steps. The cadence should happen at the end of every timebox. The cadence should trigger a, pivot, or stop decision. For DSDM, the cadence should be part of the team's feasibility and foundations practice. The cadence is a verification tool.
Closing on Measuring What Matters to Customers Over Measuring What Is Easy to Measure (76/89)
Sam Walton did not build Walmart by measuring what is easy to measure. He built it by measuring what matters to customers. When he measured what mattered to customers, he saw what was real. When he saw what was real, he made good decisions. When he made good decisions, he kept customers. When he kept customers, he won. (77/89)
The 29-person DSDM team tracked 15 metrics. Fourteen were activity metrics. The team celebrated features shipped and story points completed. The team felt productive. But 69% of loan applications were abandoned. Customers left for competitors. The company lost $2,568,000 annually. (78/89)
Then the team applied Walton's everyday low price strategy. The team created an outcome metric framework that replaced all activity metrics with four customer outcome metrics. The team used the framework for six months. The team tracked four metrics instead of 15. The team saw that all four were below target. The team focused on loan application completion and increased it from 31% to 52%. The team reduced time to loan approval from 11 days to 6 days (79/89)
. The team improved financial health score increase from 2 points to 6 points. The team increased retention rate from 63% to 71%. The team saved $1,200,000. (80/89)
The team created a metric reality dashboard that displayed the four customer outcome metrics in real time. The dashboard showed the gap between current performance and target for each metric. The team used the dashboard for six months. The team saw the gaps. The team focused on the 18-percentage-point gap in loan completion rate. The team focused on the 3-day gap in time to approval. The team focused on the 4-point gap in financial health score (81/89)
. The team focused on the 9-percentage-point gap in retention rate. The team made good decisions. The team saved $1,200,000. (82/89)
The team created an outcome-driven prioritization system that scored every feature in the backlog based on its expected impact on the four customer outcome metrics. The team used the system for six months. The team scored 53 features. The team built the top ten scoring features. The average score was 13.2. The team increased loan completion rate to 52%. The team reduced time to approval to 6 days. The team improved financial health score to 6 points (83/89)
The team created an outcome metric review cadence that reviewed the four customer outcome metrics at the end of every DSDM timebox. The team used the cadence for six months. The team reviewed six timeboxes. The team found that 26 of 41 features improved at least one metric. The team found that 15 of 41 features had no impact. The team stopped building no-impact features. The team focused on impact features. The team kept customers. The team saved $1,200,000. (85/89)
For a finance services multinational running DSDM with a large team of 16 to 50 people, creating meaningful success metrics requires the same everyday low price strategy. Measure what matters to customers. See what is real. Make good decisions. Keep customers. (86/89)
Start by having your 29-person DSDM team create an outcome metric framework this week. Then create the metric reality dashboard. Then create the outcome-driven prioritization system. Then create the outcome metric review cadence. Your 8,600-employee multinational stops losing $2,568,000 annually on activity metrics (87/89)
. A finance services multinational learned to create meaningful success metrics from an everyday low price strategy pioneer who proved that the best way to create meaningful success metrics is to stop measuring what is easy to measure and start measuring what matters to customers. When you measure what matters to customers, you see what is real. When you see what is real, you make good decisions. When you make good decisions, you keep customers. When you keep customers, you win. (88/89)