Value engineering

• Administration
• Build a value hypothesis
• Bet
• Pivot/persevere

The basic goal of value engineering is to improve efficiency and decrease operating costs through analysis. In Jira Align, value engineering can be performed on epics, capabilities, and features to improve function and lower costs, or to determine if these work items are worth building.

Administration

Value engineering is a platform setting that must be set at the portfolio level. To activate value engineering for a portfolio, follow these steps:

1. Navigate to the portfolio platform settings.
2. Next, on the Portfolio tab, click Portfolio Specific Configuration at the bottom of the page; the Maintain Portfolio Settings dialog box opens.
3. From the Portfolio drop-down menu, select the portfolio that requires value engineering.
4. The Maintain Portfolio Settings dialog box opens again, this time with a list of various parameters that can be set at the Portfolio level.
5. Near the bottom of the list is the Value Engineering parameter; set the Value Engineering parameter to Yes.
6. Click Save Settings; value engineering is now active for epics, capabilities, and features assigned to the target portfolio.

Build a value hypothesis

A value hypothesis examines whether a product delivers value that customers want to use. In Jira Align, you build a value hypothesis using a worksheet/form that walks you through several questions designed to help you find the answer. To build a value hypothesis, follow these steps:

1. Open an existing feature, capability, or epic so that the details panel displays.
2. Open the Value tab.
3. Click Build Value Hypothesis; the Build Value Hypothesis dialog box opens.
   
   
   
   
4. In the first section (If this...), enter the hypothesis you believe to be true. A good, comprehensive hypothesis should be written in the form “We believe {action} will result in {this behavior change}.”
5. In the middle section (Then this...), identify the desired outcome of the epic, capability, or feature. Select a metric type from the dropdown menu, enter a target metric value, its descriptor (for example, increase in engagement), and its allocation percentage. Use the We'll know we're successful when box to write a specific outcome or market signal.
6. In the final section (Success Metric), benchmark where the desired metric is today and when the outcome should be met. Enter a numerical metric in the Where are you today? box (this value is your Starting Metric). Next, use the calendar feature to enter a date in the We should meet or surpass our goal by box. In the Value of Outcome box, enter a value that represents how much you are willing to spend/bet to validate the hypothesis. Finally, enter the names of Analysts/Approvers that will examine the value hypothesis.
7. Optionally, fill in the Who is this being built for? section. From the Personas drop-down menu, select the personas that the epic, capability, or feature is being built for. The list of personas is filtered by the programs assigned to the epic, capability, or feature. Select specific customers from the Customers dropdown menu.
8. Click Save; the Value tab of the selected epic, capability, or feature displays, showing the outcome entered in Step 6 and two new sections called Initial Estimates and Assumptions.
9. In the Initial Estimates section, enter estimates for Cost to Research and Cost to Build in the corresponding fields. Note that if you are value engineering an epic or a capability, you have the option to toggle these values to the set estimation system (team weeks, points, etc.) instead of a dollar amount; the values are automatically pulled in from the portfolio-specific values assigned to the PI. 
10. Optionally, in the Assumptions section, enter any assumptions you may have in the text field. You can view your assumptions during any portion of the value engineering process: assumptions you create here will also appear in the Assumptions section during other phases of value engineering. From the drop-down menu that appears, select if the assumption is a normal assumption or a leap of faith.
11. Click Add; the assumption’s name and type are added to a table. A third column, State, also appears in the table. As you discover more about the assumption, update its state at any time during the value engineering process using the State drop-down menu.
12. Select Save on the work item; hypothesis building is now complete. Notice that a progress bar now displays below the Value Engineering heading; it shows that the Hypothesize phase is complete, and you are ready to move on to the Bet phase of value engineering.
    
    

Bet

The Bet section tracks expenses, research methods, and approvals to move to the third phase, Pivot/persevere. Follow these steps to fill out the Bet parameters:

1. On the progress bar that displays below the Value Engineering heading, select Bet; the Bet parameters display.
   
2. The first parameter is Should we continue to the validate phase? This is used by the analysts/approvers, set during hypothesis building, to vote on moving the epic, capability, or feature to the next phase, Pivot/Persevere. Approvers/analysts will see a heat map visualization for confidence voting. Clicking Vote opens a dialog box with a slider where you can vote on a scale from 1 to 10 on how confident you are that this item will be valuable and deliver the desired outcome, with 1 being less confident and 10 being most confident. You can only vote once a day for features and once a week for epics and capabilities. These votes appear in the rows of boxes, where each box represents one day or week accordingly and each row represents one approver/analyst. The votes have different coloring. Point to a colored box to view who voted, what the vote is, and the vote date. Average confidence vote shows to the right of the heat map. It is calculated by the average of the most recent votes; non-votes do not count against the average.
3. If you have entered a cost to research on the Hypothesize tab, you will see the Research Budget section, which you will need to complete. To add a research expense, click Add Expense; in the Add Expense dialog box that opens, add the Spend (amount) and Date of the expense, and then click Add. Entered expenses display in a list at the bottom of this dialog box. Repeat as needed to add more expenses. Close the Add Expense dialog box. The Research Spend (to date) and Remaining values update based on the expenses entered. The Estimated value will update based on values entered in Step 4 for research methods. The Research Budgeted value carries over from the Cost to Research box entered under the Initial Estimates of the Hypothesize phase. The Research Spend plot graph also updates as new expenses and dates are entered.
   
   
   
   
4. If you have entered a cost to research on the Hypothesize tab, you will also see the Research Methods section. Use the Research Methods section to capture additional estimates for research methods. Click the blue + Add link to activate a new row where you can enter a research method and cost. Repeat as needed to add additional rows. The sum of the research method costs updates the Estimated field in the Research Spend section.
5. Use the final section to upload or drag and drop supporting files.
6. Click Save. At this point, you are ready to move on to the Pivot/Persevere phase.

Pivot/persevere

The Pivot/persevere phase tracks your estimates against the actual spend. Follow these steps to fill out the pivot/persevere parameters:

1. On the progress bar that displays below the Value Engineering heading, click Pivot/Persevere; the pivot/persevere parameters display.
   
   
   
   
2. The first parameter is Should we continue investing? This is used by the analysts/approvers, set during hypothesis building, to indicate if investing should continue for the epic, capability, or feature. Approvers/analysts will see red and green buttons, which are used to indicate continue (green) or stop investing (red). You can only vote once a day for features and once a week for epics and capabilities. These marks are entered in the rows of boxes, where each box represents one day or week and each row represents one approver/analyst. The votes have different coloring. Point to a colored box to view who voted and the vote date.
   
   
   
3. The next section is Estimate vs. Actuals. The Actual Effort/Spend to (to date) values carry over from story points and cost tied to the epic, capability, or feature, which automatically populates. The Estimated value is the Cost to Build estimate entered in the Hypothesize phase.
   
   
4. The Actual Value (to date) populates with the updated metric values and is calculated as (Current Metric–Starting Metric) * value of one point. Value of one point = value of outcome of a specific metric / (Target Metric–Starting Metric). To update the value, click Update, enter the new current value for the metric along with the Date, and then click Update. Close the dialog box, and the new value displays in the Actual Value (to date) field, along with the percentage of change in value. The Actual Value (to date) values plot on the line graph to the right. Ideally, the Actual Value should track closely to the Ideal Value line, which represents the Value of Outcome entered in the Hypothesize phase. The Actual Spend line will populate only when stories are accepted. 

   Select the icon next to a metric to view the Metrics Dashboard, where you can view the progress of all of your metrics over time. On the dashboard, all target metrics are listed, along with a row of values reflecting the most recently reported Actual Metric value during each week that the hypothesis is being tested. To the right of the weekly values is an indicator reflecting the trend of the most recent value. If the most recent value is higher than the previous week’s last reported value, the indicator is a green triangle. If the most recent value is lower than the previous week’s last reported value, the triangle is red. If no change has occurred, the indicator is a gray line.
   
   A line graph appears for the metric you’ve selected. However, you can select the arrow icon next to the name of another metric to display a line graph for additional metrics. On each graph, the actual values reported for each metric are displayed as a purple Actual Value line, with individual plots reflecting the actual metric values you’ve reported. The vertical position of each plot reflects the actual metric value itself; the horizontal position reflects the date the metric was reported. Point to a plot to view the value associated with it.
   
   A gray Ideal Value line depicts the ideal progress rate as you move from your baseline toward your target metric. A pane on the side of the graph depicts the metric’s target value and baseline/initial value, the current value, the amount of time remaining, and the current percentage of progress against the target goal.