Search and Discover Solutions: Gaining Commitment — How to Start, Part 2
Dick Bourke posted on October 23, 2015 |

In Part 1, I described how to create awareness around the potential of search tools — the first step in a nurture campaign.

The next step is to create a desire for action by identifying the values and return on investment (ROI) of a search and discover solution (SDS). In this column, I’ll discuss techniques for achieving a solid ROI with design reuse.

Design reuse is universally stressed as the core value of an SDS. Variations in identifying ROI will — and should — differ in line with company needs and circumstances.

You can use a range of justification tactics to classify the values: cost avoidance, cost reduction, or combinations. Each tactic or combination has its own merits, tempered by the related costs to upgrade supporting processes and software. Of course, we must recognize that cost avoidance and reduction are not mutually exclusive.

Cost Avoidance

Figure 1. (Image courtesy of Siemens PLM Software.)

Figure 1. (Image courtesy of Siemens PLM Software.)

Without design reuse capabilities, a company is likely incurring unnecessary costs every day and in every function (Figure 1). This includes:
  • Recreating product designs and supporting documents (can be as much as 11 times the cost of the original)
  • Creating/maintaining duplicated part numbers (past surveys estimate the cost from $6,000 to $25,000)
  • Struggling to maintain the current part classification/coding schemes and file systems to support data retrieval

A major tactic could be to avoid the inflated costs of direct material spending that can happen if design reuse is not deployed to aid component and supplier management. Specifically, to reduce part costs by leveraging higher volumes of preferred parts from fewer suppliers.

The bulk of value propositions presented by SDS vendors relate to the cost avoidance of duplicating parts — a simple benefit that can stir desire among target customers.

I'll take the conservative approach, however, and assume C-level executives (i.e. decision makers) will expect figures specific to their company. An approach that’s inspired one SDS vendor (Directworks) to frame their ROI analysis in terms of “executive expectations.”

How Do You Calculate Cost Avoidance ROI?

Formulas for calculating savings are simple—although they should only be treated as a starting point. Here’s an example from PTC, similar to most vendor presentations.

Pi x 12 months x D% x Pic = Yearly savings

·         Pi is the new part introduction rate per month

·         D% is an estimate of current duplicate parts

·         Pic is the new part introduction cost, usually somewhere from $6,000 to $25,000

Notice that the last two factors are estimates—assumptions that an evangelist will need to validate for credibility's sake before seeking approval.

What about D%, duplicate parts?

Estimating duplicate parts without facts is a questionable justification tactic. Whose estimate, or best guess, should a target customer believe? Fortunately, factual approaches are also available.

Many of the shape-search vendors identified in Useful Search Applications for Finding Engineering Data - Part 2 offer trials and analysis of product databases. For text-oriented tools, I previously identified Convergence Data Services and Noetic-Data, who provide varying levels of analysis on a tiered pricing basis.

What about Pic, identifying avoidable costs?

There is no need to reinvent the wheel here. Try one of the detailed templates already available in the public domain: Reduce Program Costs through Parts Management. They provide a complete listing of the cost elements in every company function.

Which Tactic(s) Should a Company Choose?

Figure 2. (Image courtesy of Source: Actify, Inc.)

Figure 2. (Image courtesy of Source: Actify, Inc.)

As usual, it depends. Each tactic could have a role in the company’s design reuse initiative. Each has its pros and cons and you aren’t limited to one tactic.

Addendum — Geometric (Shape-Based) Searching

If you would like to know more about how geometric (shape-based) searching works, here’s an informative presentation: 3D Data Mining Part and Information Re-Use in a PLM Context from 3DSemantix.

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