Sprint simulator#

Compare work items on risk probability filtering by value stream and sprint.

To enable the Milestone risk predictive analytics system in HCL™ Accelerate, you need to install and enable the Milestone risk plugin on the Settings > Integration page. Additional details are found here.

Cost effective decisions in the software development process involve determinations including business objectives, design, technical and acceptance criteria, and allocation of resources that are preferably implemented in the early phases of a project. Extra resources applied to complex objectives in early development phases while evaluating the effectiveness or non-effectiveness of high risk objectives in a timely manner aid decision-making to pursue or cancel efforts to avoid unfavorable impact on the project. While deferred decisions on objectives or specifications may lead to waste, implementation of action plans are still possible late in the development process because detailed data is accumulated with the unit of value traversing the value stream.

In order to facilitate a balance between economical early decisions and better informed late decisions in the software development process, the HCL Accelerate Milestone risk analysis predictive analysis system is a risk mitigation tool that uses the full history of value processed and delivered by a value stream to assess the value-realization risk associated with items currently in the value stream. By pinpointing work items with levels of risk early in the development cycle, teams are strategically positioned to triage vulnerable work items and identify risk mitigation interventions providing maximum leverage with minimal costs. Because risk assessments are updated on a regular cadence with the tool, teams utilizing the dashboard on a regular basis can evaluate the impact of mitigation efforts affecting the assessment dynamically in near real time scenarios.

The Milestone risk analysis tool is a predictive analytics system assessing the milestone delivery risk of in progress work based on three sources of information including:

  1. The type and status of the work.
  2. State of the value stream where the flow of work is processed.
  3. The human resources processing the work.

The aforementioned information sources are unique to each software development team and the resulting risk analysis provided by the tool is specifically tailored to the inherent characteristics of that working group. As the team grows over time, the Milestone risk analysis evolves by using all the latest data about how the team works to adapt risk assessments to the characteristics of that team.

In order to generate milestone risk predictions for a value stream, the value stream must satisfy the following four requirements:

  1. An integration with a work tracking tool including Jira, Rally, and so forth.
  2. A configured value stream in HCL Accelerate with a minimum of two defined stages.
  3. A definition of the cycle time for the value stream.
  4. A set of milestone deadlines defined via specified sprint end dates in the users work tracking tool.

Based on these requirements, a unique predictive model is constructed for each value stream that conforms to the boundaries defined by the aforementioned criteria. Once the predictive model is established, daily predictions are generated and evaluated against the targeted deadline to asses risk levels associated with a specific dot reaching the milestone by the deadline.

To use Milestone risk predictive analytics system, complete the following steps.

  1. On the HCL Accelerate Home page, click Insights > Analytics > Sprint simulator.

    The Sprint simulator page opens, that enables you to filter value streams and sprints, run queries, save searches, and customize the displayed data. Sprint simulator data, search, and filters available on this analytics dashboard are illustrated and detailed in the following figure and two tables respectively. The first table details common search and filter fields and the second table addresses fields specific to sprint simulator filters and data.

    Item Field Field type Description
    1 SAVED QUERIESsaved queries Drop-down View saved or save new queries including text and applied filters.
    2 Search Text entry Use Kibana query language (KQL) for simplified query syntax and support for scripted fields. If KQL is turned off, Apache Lucene is the search engine used for queries.
    3 KQL Drop-down Select KQL or Apache Lucene as the search engine for queries.
    4 Time filterstime filters Drop-down Time filters including Quick select, click either < or > to select the Previous time window and Next time window respectively, Commonly used, Recently used date ranges for time ranges. You can also use Refresh every to set the refresh periods for the data and Start and Stop refreshing data.
    5 Time Text Displays the time range based on your applied time filters.
    6 Show dates Text click Display dates in the time field.
    7 Refresh Button Refreshes the data on this page.
    8 CHANGE ALL FILTERSchange all filters Drop-down Modify filter options including Enable all, Disable all, Pin all, Unpin all, Invert inclusion, Invert enabled/disabled, and Remove all.
    9 Add filter Drop-down The Edit filter drop-down allows you to Edit filter values including Field, Operator, and create a custom label. Also, you can Edit as Query DSL and save all settings and queries.
    Item Field Field type Description
    10 Value stream Drop-down Select value stream filters.
    11 Sprint Drop-down Select sprint filters.
    12 Work items count Text Number or work items.
    13 Sprint work items Tabular interactive interface Table including the Time, measures.id (Issue number), measures.name (Description), sprint, storyPoints, priority, status, owner, risk

    Note: When you click on options drop down in the upper right corner of fields listed in Items 10 through 12 of the aforementioned table, an OPTIONS drop-down displays with available selections according to the following:

    • Items 10 - 11: Maximize panel
    • Items 12 - 13: Inspect and Maximize panel
    • In the Sprint simulator page, define the data scope by completing the following steps:

    • In the Sprint filters area, click the Value stream drop-down and select the required value streams.

      By default, the data for all value streams to which you belong are available for selection.

    • In the Sprint filters area, click the Sprint drop-down and select the required sprint.

      By default, the data for all sprints associated with the value stream that you selected are available for selection.

    • Click Add filter if you need to edit the filter and perform the following:

      • In the Field drop-down, select the field.
      • In the Operator drop-down, select the operator.
      • If you require a custom label, click the Create custom label button slider and in the Custom label text field enter the label name.
      • Click Save.
      • Alternatively, you can enter a DSL query by clicking Edit as Query DSL and perform the following:
        • Enter your query in the Elasticsearch Query DSL text field.
        • If you require a custom label, click the Create custom label button slider and in the Custom label text field enter the label name.
        • Click Save. Note: All of the applied filters from both the Sprint filters and the Add filter sections are displayed to the right of the change all filters drop-down. You can delete one or more of the filters by clicking x on the right side of any of the individual filters.
    • If you want to run a query, in the Search field, you can use either Kibana query language (KQL) Apache Lucene by entering your query in the field.

      Note: KQL is the default query language. If you want to use Apache Lucene, click KQL and click the button slider to Off position and Lucene is displayed to the right of the Search field and replaces KQL as the query language.

    • Click time filters and perform the following:

      • Select the required time range filter from the Quick select, Commonly used, or Recently used date ranges sections. If you use the Quick select section, perform the following:
        • Click either < or > to select the Previous time window or Next time window respectively.
        • Alternatively, you can select the required criteria in the two drop-down fields, enter the number associated with the time interval in the text field, and then click the Apply button.
      • If you require the data to refresh at a predetermined time interval, in the Refresh every section time unit drop-down, select the required interval.
      • In the Refresh every section time field, enter the number associated with the time interval selected in the previous step.
      • In the Refresh every section, if you do not want the data refreshed on a time interval, click the Stop button. Conversely, if you want the data refreshed on a time interval, click the Start button. Note: When you select a time range filter from the Commonly used or Recently used date ranges sections, the Value stream flow page is automatically refreshed and displayed with the applied filter.
    • If you want to display dates in the time field, click Show dates.

    • Click the Refresh button to update the data with the aforementioned filters and queries.

    • You can save the search with all of the applied criteria by clicking saved queries and perform the following:

      • Click the Save as new button to display the Save query window.
      • In the Name field, enter a descriptive name for the query.
      • If you want the applied filters saved, turn on the Include filters button slider.
      • If you want the applied time filter saved, turn on the Include time filter button slider.
      • Alternatively when you click saved queries, if this is a previously saved search, there is a check mark to the left of the saved search Name and you can click the Save changes button to save the updated search criteria. Note: To delete a saved query, hover the pointer over the name and click delete saved query to remove it from the list.
  2. On the fields listed in the following table, click options drop down and select Inspect to display the respective data view drop-downs and perform the following:

    Item Field
    12 Work items count
    13 Sprint work items

    Note: When you click options drop down and then select Inspect for items in the above table, the following information is displayed:

    • For Item 12, a Work items count window listing the Unique work items count in the Data view drop-down in the upper right corner of the window. To download comma-separated values for Work items count, click Download CSV and select either Formatted CSV or Raw CSV.
    • For Items 12 and 13, when you click options drop down and select the Requests view drop-down in the upper right corner of the window, you can view the following information:
    • To display the requests view for any of the metrics, click the View: Data drop-down and select Requests to view number of requests made, total time the request took, request success or fail status, and the three tabs with associated data detailed in the following table:
    • In the Sprint work items tabular data, the risk field identifies dots in the following categories:

    • Low risk dots have a greater than 80% possibility of reaching the milestone prior to the deadline time.

    • Medium risk dots have between a 60 - 80% possibility of reaching the milestone by the deadline time.
    • High risk dots have less than 60% possibility of reaching the milestone by the deadline time. Note: These risk assessments are probabilistic and not deterministic. A Low risk assessment does not guarantee that a dot will reach the milestone by the deadline time and a High risk does not guarantee that the dot will miss the deadline time. Generally, it is expected that over 80% of all dots categorized as Low risk are successfully completed by the deadline time and not all Low risk items are guaranteed to be completed by the deadline time.