Support for value engineering

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Value engineering is simply the use of a hypothesis to drive how blocks of work are funded in portions. Value is measured with rapid feedback loops and continuously compared with costs incurred. This information is leveraged regularly to drive investment and pivots.

In the absence of good data, people tend to get their pet projects funded. Particularly in the enterprise, we often see spectacular amounts of money poured down the drain on systems replacement projects.

According to Douglas W. Hubbard's book "How to measure anything," a study found that 50% of total product development time is spent on "fuzzy" front end activities. This leads to poor investment decisions and long product development cycles that create multiple negative outcomes including: reduced return on investment, long feedback loops from customers, and business cases that are viewed as science fiction over time. Even worse, a significant amount of time is wasted on detailed planning, analysis, and estimation, which provides large amounts of information with extremely limited value.

Most large project business cases have 40 to 80 variables, such as initial development costs, adoption rate, productivity improvement, revenue growth, and so on according to Hubbard. Most variables had an information value of zero. The study also revealed that the variables that had high information values were routinely those that the client never measured and the variables that clients spend the most time measuring were usually those with a very low information value.

In the modern economy, the biggest risk is the failure to create something that delivers value to users.

Value engineering and Lean thinking allows an enterprise to rapidly discard ideas that do not deliver value or will not be adopted sufficiently quickly so resources are not wasted on them. However, the principles behind the Lean Startup can be applied to all kinds of activities within the enterprise, such as building internal tools, process improvement, organizational change, systems replacement, and programs.

Value engineering consists of building a customer-centric hypothesis that includes a definition of MVP and often is accompanied by a Lean canvas. Often the OTM (one metric that matters) is used to build the value statement for the hypotheses. Value engineering with rapid feedback loops enables a virtuous cycle of innovation in which "Run" activities enable growth. "Growth" activities fund innovation and the "Transform" actives are then operationalized to drive new "Run" activities. With Value engineering  and Lean thinking an enterprise can:

  • Adopt a mindset in which all our ideas are hypotheses
  • Safely explore opportunities in conditions of extreme uncertainty
  • Invest the minimum amount of effort to obtain the maximum amount of learning
  • Create a clear vision and a shared understanding of the problem
  • Make decisions on information gleaned from fast, inexpensive experiments
  • Pivot or fold on bad ideas faster
  • Engage customers early to act as co-creators of value
  • Focus on learning rather than revenue
  • Focus on user engagement over quick financial gain

To learn more about driving a hypotheses approach for lean portfolio management backed by innovation accounting check out "Lean Enterprise" by Jez Humble, Joanne Molesky, and Barry O'Reilly.

“In this world, there's so much work that's spread out across many different environments, and Jira Align allows you to pull it all together to tell a story with the data.”

VP of Product Agile Services and Delivery

 Fortune 500 Corporation

How Jira Align supports value engineering

Check out these purpose-built features that enable value engineering at scale:

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Build a Lean hypothesis

Build a clear hypothesis statement of expected value versus expected cost for epics / features.

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Account for research costs

Account for any research required to fund the first tranche such as design ride alongs or architecture designs.

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Measure results in real-time

Use APIs or manual measurement to measure the OTM (one metric that matters) over time.

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Decide to stop, pivot, or double down

Each stakeholder can vote to continue or stop based off of the real time cost versus value ratio.

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Measure results versus the portfolio

Easily compare the cost versus value ratio against other epics / features in the portfolio.

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Capture value analytics

Use the value metrics in combination with other analytics in the Jira Align platform to plot your strategy forward.

Explore the benefits for other roles

Portfolio management


Communicate the value of funding strategic initiatives to investors, analysts, and employees.

Product management


Manage idea intake, prioritize your feature backlog, and track progress with live roadmaps.

Program management


Track and resolve program risks, impediments, and dependencies while keeping everyone informed.

Release train engineers


Ensure programs run smoothly and resources are perfectly allocated to nail on-time delivery.

Finance


Ensure Initiatives maximize value, right-size scope and stay within budget from end to end.

Executives


Drive enterprise value of your high-level mission and vision while connecting strategy to execution.

Transformation teams


Drive digital transformation with a framework customized to scale agile in your enterprise.

Delivery teams


Execute against sprint work that tracks back to your organization's high-level strategy.

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