Optimizing Value Stream with Orasi

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By Joe Schulz

Value Stream OptimizationEven as DevOps reaches a pinnacle in acceptance (as of 2018, only three percent of firms had not adopted DevOps and had no plans to do so), many organizations are still struggling to get high-quality software out the door. DevOps has been promoted by many experts and consultants as a solution to the cumbersome inefficiencies that were common with waterfall methods. However, as is common for many operational activities, applying a new approach or technology doesn’t automatically resolve entrenched problems.

Nowhere is this more obvious than in value stream management (VSM). This approach, which focuses on removing the waste from processes to increase their efficiency, sounds like a panacea for resolving software delivery challenges. In practice, it often falls short of its goals.

Why is this? There is nothing wrong with the concept of the value stream. The idea of breaking down a complex process into its components and optimizing each one of them, thereby optimizing the chain, is a long-recognized pillar of lean production. In my view, the problem isn’t with VSM or even DevOps.

The problem is that in moving from waterfall to DevOps and/or agile, many organizations figuratively “throw the baby out with the bathwater.” They are uncertain how to adjust for the extreme acceleration that occurs when teams move from rudimentary software processes to modern ones, so they either jettison important elements of software engineering or adapt them incompletely.

Why Continuity Matters

By way of example, consider measurements and metrics. The traceability and proactive remediation enabled by measurements and metrics are two of the most important aspects of software development. However, it’s not just the development and test metrics that matter, but also the business metrics—metrics of quality, user acceptance, security and ease of use. Since the dawn of software development, those two groups of data have been inextricably linked, but some modern software teams appear to have forgotten that lesson.

No amount of process improvement metrics can ensure a software release is secure or that users will like it. Yet, if a major software upgrade is flubbed, it can impact operations so negatively that sales momentum stalls. (If the company sells the software it develops, the ripple effect is even stronger.) Even more disconcerting, after a major data breach, a firm can find itself out of business.

Don’t get me wrong. I am not suggesting that flow and other DevOps metrics don’t matter, because they do—very much. I am suggesting that many teams and their development managers have become too divorced from the business metrics, which can have staggering negative consequences.

From There to Here

In the days of waterfall, development artifacts, defects and other data were warehoused in an offsite location, and after each release (which might take days, weeks or even months), teams would engage in several days of data extraction. Then, a separate team would attempt to map the development artifacts to the defects and enable traceability. After hours or days of organization and cross-mapping in Excel spreadsheets, reports would be generated for management and the C-suite. Once stakeholders and management completed their evaluation, the team would be cleared to make adjustments before the next release cycle.

Now, our development paradigm has changed so dramatically that many teams aren’t giving metrics their due. That’s an issue with defect metrics that could impact the user experience or software reliability. It’s a serious, potentially game-ending problem when the metrics are related to security.

Completing the Value Stream

To create and administer the complete value stream, software teams must be supported in three areas beyond the traditional DevOps framework where iterative development activities are the primary driver of traceability measurements. With these elements in place, management can map their software teams’ efforts to the business metrics that are the final measurement of success:

  • Organizations must have a mechanism for integrating development and testing tools so that defect measurements can flow back to the development team in real-time—matching the speed of DevOps.
  • Critical software activities that still take place outside of development and testing processes, such as generation and approval of change orders, must also be monitored for inertia, with approvers being held accountable for holding up paperwork that delays releases.
  • Security defects must be given parity with, and preferably priority over, all other code defects. All defects that impact the user side, such as functionality and launch speed, are important business metrics. But security must be paramount.

If you are a development team member reading this, or even a development manager, you may think business metrics and the related activities that happen outside your purview, don’t apply to you. I urge you to think again. Software has become a critical pillar of many companies’ operational success, and that connection is only growing stronger by the day. Everyone involved in software development, from the developer to the VP of Operations and on to the CEO, must view the entire process through the lens of business.