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Using end-to-end metrics to understand and mitigate software delivery (capability) risk

Plandek, December 18, 2019

By Charlie Ponsonby, Co-CEO Plandek

Introduction

Governance and risk management is an increasingly active research area in Agile software delivery – particularly in large scale organisations.  Moving to an effective Agile methodology is a major strategic decision.  It takes a huge amount of time and effort and inevitably questions are asked (from the C-suite down) about its effectiveness and reliability for critical software delivery initiatives.

Moreover, Agile by its very nature, involves decentralising responsibility to small self-determining teams working in a more organic (agile) way than would be the case in a more traditional waterfall environment.  This decentralised model (which is quite rightly at the heart of the Agile philosophy) can make understanding software delivery risk difficult, without effective metrics in place.

As a result, we often hear of the exasperation with existing RAG (Red, Amber, Green) progress reports – with workstreams classified as “Green” for weeks in a row, before flipping to “Red” with apparently no warning!

This short post discusses the analytics and metrics that can be applied to try and ensure that such surprises do not happen, as delivery managers have a much better understanding of the underlying risks within their software delivery teams (capability).

Delivery Capability Risk

For the purposes of this discussion, we are defining “delivery risk”, as the risk of delivering software increments:

  • later than expected; and/or
  • of worse quality than expected; and/or
  • requiring more effort/resource than anticipated.

Understanding software delivery risk in totality is a complex task, with a range of internal and external factors that drive delivery risk.  This paper is interested in a key internal risk that is directly controllable by the delivery team, that we term Delivery Capability Risk (DCR).

The concept of DCR is summarised in the graphic below.  There is a great range of Enterprise Agile Planning solutions that help you manage your delivery journeys (programmes).  They track scope, effort and apparent progress.  What they are unable to do is really understand how effectively the teams writing and releasing the software are working together.

DRC analysis lifts the bonnet (hood) on your delivery capability to understand the very real risks sitting across the teams responsible for design, development, testing, builds and deployment.

In our view, only when you fully understand these delivery capability risks, can you have a real understanding of broader delivery risk.

Graphic showing the concept of Delivery Capability risk assessment

Figure 1. Graphic showing the concept of Delivery Capability risk assessment

 

Understanding Delivery Capability Risk in complex IT programme management

There are a set of metrics that can quite accurately track delivery capability risk (DCR), but they are tricky to surface without specialist BI solutions like Plandek.

Plandek for example works by mining data from toolsets used by delivery teams (such as Jira, Git, CI/CD tools and Slack), to surface the metrics critical to identify and manage DCR.

It creates a balanced set of metrics that determine delivery capability risk, using both quant data from the underlying tools sets such as Jira, Git etc – and also from the engineers themselves via constant polling through Slack or other collaboration hubs.

The metrics fall into five logical categories which when synthesised together, give an accurate measure of DCR when tracked over time.  These categories are:

  1. Backlog health analysis – metrics and analytics to understand as far as is possible the state of team’s backlog, especially as it relates to the current and next programme cycle;
  2. Talent – quant metrics to understand your delivery teams’ morale and views on process effectiveness (collected via polling on collaboration hubs);
  3. Process efficiency and transparency – metrics that reveal the effectiveness of the end-to-end delivery process (e.g. Flow Efficiency and Lead Time analysis) which reveal bottlenecks and friction in the process;
  4. Throughput and time to value – metrics showing volume of work being produced and time taken to deliver across the end-to-end SDLC;
  5. Delivery (sprint) accuracy – metrics showing teams’ ability to meet their own sprint goals (for Scrum Agile) which is a key determinant of likelihood of delivering over longer time periods (e.g. Programme Increments).

Examples of these metrics are shown in Figure 2 below.

Example end-to-end software delivery metrics that determine delivery (capability) risk

Figure 2. Example end-to-end software delivery metrics that determine delivery (capability) risk

This balanced scorecard of capability risk metrics add a new dimension to overall programme risk management.

As Figure 2 shows, these metrics are principally designed for use in an Agile delivery context (with concepts of Cycle Times, Sprint Completion etc), but many can also be applied in a hybrid “Scrumfall” context (often adopted by larger organisations to deliver major projects).

For example:

  • Metrics relating to backlog health are clearly key in any context (and reveal hidden risk);
  • real-time understanding of engineer morale and engineer feedback as regards the delivery process are also critical leading indicators of (hidden) delivery risk; and so too are
  • changes in time spent (and the efficiency of) fixing bugs and technical debt.

These are all “under the bonnet” metrics that when viewed together, give the experienced Delivery Manager a view on the health of the delivery “engine” – is it firing on all cylinders, or running on empty…?

Applying delivery capability risk to overall project risk management frameworks

Programme management techniques typically map the various workstreams and understand interdependencies and the critical path.

These techniques create well organised Gantt charts showing the theoretical progress of the project relative to planned milestones.  However, what these techniques cannot do, is effectively track the health of the underlying technology delivery capability.

i.e. the Gantt chart may show that we just hit a key milestone, but an understanding of the health/stress of the underlying delivery team may paint a very different picture.  It may show that this was achieved in an unsustainable way (low morale, declining process efficiency, increasing technical debt etc) – hence the team is unlikely to hit the next milestone.

This is why an understanding of delivery capability risk (i.e. understanding the health of the underlying delivery “engine”) can be a vital extra dimension in complex IT programme management.

This is indeed why Plandek is used as a delivery risk management tool to be applied in conjunction with existing Enterprise Agile Planning tools (such as Jira, Jira Align, Rally etc).

Introduction to Plandek

Plandek is the leading Agile metrics BI and Analytics platform to help large Agile technology teams better manage delivery risk and improve their effectiveness.

Plandek works by mining the data history from dev teams’ toolsets (e.g. Jira, Git) to reveal and track metrics that are highly predictive of improved Agile project outcomes.  These metrics are often not visible or accurate with current toolsets.  Plandek is working with a wide range of organisations, to track and actively manage these Agile metrics, to manage software delivery risk and improve performance.

Read more by Charlie Ponsonby:

You can also check out Charlie’s article on the importance of metrics to Agile teams on InfoQ, which recently trended globally.

Read more about our team.

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