How?

Value Engineering

Calculating the time-based value that works.

Ian H Smith

At Being Guided I have been working on how our customers can clearly map out a solid use case, financial justification and technology preferences for high-value products and services across healthcare, manufacturing and technology industries.

Recently, this has included Artificial Intelligence (AI): meaning AI that actually works now. This requires Fierce Reduction applied to social media: block-out all of the technobabble from the IT industry commentariat, who are far removed from the reality of business!

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Design Thinking

At Being Guided we believe that all digital landscapes require a broad set of motivated, empowered stakeholders to engage in Design Thinking. As the name implies: this is thinking (and acting) like a designer. Being curious, restless and constantly challenging business-as-usual. It is all about solving problems in a human-oriented way.

The Stanford d.school1 Design Thinking method provides six (6) iterative stages: Empathize; Define; Ideate; Prototype; Test; and, Implement. This offers a structured yet flexible framework to better understand users, challenge assumptions and redefine problems.

This is all about applying the six stages of Stanford d.school Design Thinking:

Empathize.
Purpose: Understanding the users and their needs.
Define.
Purpose: Clearly articulating the problem to be solved.
Ideate.
Purpose: Generating a range of creative ideas to solve the defined problem.
Prototype.
Purpose: Turning ideas into tangible products.
Test.
Purpose: Gathering feedback and refining the prototype.
Implement.
Purpose: Finalising the solution and launching it.

Design Thinking enables all stakeholders exploring any business process as a candidate for your product or service offering to achieve a positive, open conversation. As I set-out in my blog post Fierce Reduction, this is also a time to challenge business-as-usual and apply a simplification of processes, tasks and systems wherever possible.

Value Engineering

Value Engineering was originally conceived by Lawrence D. Miles2, a General Electric engineer. Miles' techniques have saved design engineers, manufacturing engineers, purchasing agents and service providers millions of dollars.

To quote Miles, it was neccessary to show "why so much unnecessary costs exists in everything we do and how to identify, clarify, and separate costs which bear no relationship to customers' needs or desires."

Value Engineering eliminates waste and determines value over price. This can apply to calculating the cost of purchasing (or not purchasing) any high-vale product or service in timely manner. It is quantifying time-based value versus the cost and inaction of remaining with business-as-usual.

As Value Engineers, we set the scene mapping your ideal customer's needs with your offering. This is where we apply Design Thinking to enable you to build receptivity, rapport, trust and truth with buyers - early and often.

From a financial perspective, we start with a simple question for the buyer:

What is the cost of NOT buying the your product or service?

Firstly, let's look at the Return On Investment (ROI) Model - a general formula:

ROI = (Cost of Investment / Net Profit​)×100%

To adapt this formula for an As-Is vs. To-Be comparison, consider:

Net Profit: This will be the difference in profits between the Future State (To-Be) and the Current State (As-Is).

Cost of Investment: This is the cost incurred to move from the Current State (As-Is) to the Future State (To-Be).

Given the above considerations, the formula becomes:

ROI = (ProfitTo−Be​ − ProfitAs−Is​​ / Cost of Transition) × 100%

Where:

Profit To-Be = Profit or (benefit) in Future StateProfit As-Is = Profit (or benefit) in Current StateCost of Transition = Cost to move from As-Is to To-Be

Note: If you're measuring benefits other than strict monetary profits, such as time saved or other intangible benefits, ensure you can convert these benefits into a monetary value for this to be valid.

To calculate the Return On Investment (ROI) from AI-Powered Digital Innovation with the specified inputs, we can formulate several equations. Let's define the variables first:

BVAs-Is = Current State (As-Is) Business Value generated per annum without Solution.BVTo-Be = Future State (To-Be) Business Value generated per annum after investing in Solution.

COS = Cost of Solution.ROI = Return on Investment as a ratio relative to the Cost of Solution.

CoD = Cost of Delay per day when not investing in Solution.CoDN = Cost of Doing Nothing per day when not investing in Solution.

CoDday = Cost of Delay per day when not investing in Solution.

CoDNday = Cost of Doing Nothing per day when not investing in Solution.

Calculating ROI from Solution: Net_Gain - BVTo-Be - BVAs-Is

Calculating ROI: ROI - Net_Gain - CDI / CDIThe ROI is expressed as a ratio. Multiply by 100 to get a percentage.

Cost of Delay (CoD): This represents the loss per day by delaying the Solution purchase. Assume the delay starts from the beginning of the year and goes on for d days:CoD = BVTo-Be - BV As-Is (d x CoDday) - CDI / CDI

Cost of Doing Nothing (CoDN): This is the loss per day for not implementing the Solution. Similarly, for d days:CoDN = BVAs-Is - (d x CoDNday) - CDI / CDI

Mutual Value Discovery

The combination of Design Thinking and Value Engineering provide a solid foundation to create what can be described as a Mutual Value Discovery. This simply means that building receptivity, rapport, trust and truth with buyers - underpinned by a co-created, hard-headed ROI Model - results in sellers winning business faster and successfully defending value over price.

As the infographic at the top of this blog post illustrates, the Design Thinking and Value Engineering combined with a pursuit of Mutual Value Discovery as a win-win between buyer and seller enables the high-value, high-touch sell to have clearer outcomes in sales.

References

  1. Stanford d.school.
    https://dschool.stanford.edu/about
  2. Miles, L.D. (1947). The Lawrence D. Miles Value Engineering Reference Center Collection.https://minds.wiscon.edu/handle/1793/301