DevOps Outcome- Leading and Lagging indicators

I’ve been reading this bestseller: The 4 Disciplines of Executionby Chris McChesney, Sean Covey, and Jim Huling (Free Press, 2012).This book greatly inspires me to connect the DevOps outcome through the four step model mentioned in the book. There can be other techniques to underpin the outcomes but let’s try to understand the devOps outcomes applying this model

Building context, Lag Measures is the state we are trying to accomplish, such as faster time to market, however, it is always in the past. Once we see a Lag Measure, there is nothing more that can be done about it. Lead Measures, on the other hand, are both predictive, meaning they lead to the accomplishment of the Lag Measure or desired state, and they are influenceable.

“Once a team is clear about its lead measures, their view of the goal changes.”

Lag Measures of devOps 

Mostly through the experience all of us have fair amount of understanding about the lag measure, not much focus has been put on the lead measures which leads to our desired state. One way to look at the lag indicators is connected devOps is “The Three Ways”, without reinventing the wheel.

First Way- Flow

For simplicity we consider flow often termed as the “The First Way”, which focus on the performance from left to right, in the delivery pipeline as one lag measure

Lead Measures for first way

  • How many items are in Visual Backlog
  • How many teams are available
  • How much is the velocity of delivery
  • How much % requirement coverage
  • Time lapsed between customer request and delivery
Second Way Feedback    

The second lag measure can be building efficient feedback loops directly connected to user experience, the desired state is to shorten the feedback loop and it is often termed as the “The Second way”. This lag measure is focusing on optimizing feedback in order to take corrective actions in time with wholistic understanding of value

Lead Measures for second way

  • Are customer included during pilot
  • How many actionable feedback received
  • How many improvement initiative proposed
  • Time lapsed to build critical mass of customers per MVP / features
Third Way Experiment     

The Third lag measure might be linked to experiment and implement new methods which introduce robustness in the product or a service like forcing failures to test resiliency. This way encourages to foster the culture of continuous improvement. There can be various leading indicators to ensure we succeed to achieve the desired state of continuous improvement.

  • % investment in Skill
  • % investment in partnership
  • Number of opportunities added
  • Number of features produced
  • % usage of MVP /features produced

Capitalizing through Leading indicators of devOps

Keeping in view the widely important goal of devOps is “Creating a culture of collaboration between various teams that deliver value in different phases of a product or service lifecycle to maximize outcome”

To accelerate the journey of maximizing devOps outcome, define the leading indicators for the lag measures. There can be many lead indicators depending on the maturity of the organization. The second step is to assess and focus on high value leading indicators, balance the outcome and stay relevant.

Example of a leading indicators

Every organization is striving for better outcomes within shorter lead times, teams and culture of the organization are at the focal point of this large change initiative. Defining key KPI which will support the journey is of high importance. The first way emphasizes on flow, which is how to structure work, making work visible is the first step in the process, it is also important to visit the batch size, limit the work in progress and sort the backlog. It is critical to work on process which support business outcome, prevent inconsistency & loss of integrity. The above section indicates some of the lead measures for continuous improvement & experimentation. It is extremely important to institutionalize daily work improvements,designing and conducting experiments which in turn become MVP.

Some other examples of lead measures are as below. The devOps practices can be adopted as  key leading indicators. Choosing the right practice or creating one is context dependent. Utilizing data points for fueling devOps journey is advisable

Want to finish this article would like to add that lead and lag measures are considered at different level of abstraction and it is important to understand the context before putting it together.