In the previous articles on dFM, we covered the basic concepts and how to determine the basic factors. This posting explains a simple process for building a matrix from these factors that will allow you to "cost" a scenario. A "scenario" is an option for building and architecting a software application. We then score this scenario using a score-card (described here), to compare the various scenarios.

This is a common weighted scoring system for decision support. Its not a perfect system; the subjective weighting are controlled to a degree by a democratic voting system, but a single factor could still play an unfair pivotal role in a final score for a potential scenario. This technique is shown to spark some ideas, not as a prescriptive technique.

Step 1 -  Brainstorm a set of factors that influence - cost, time, performance, security, and reliability.

Step 2 - Group similar factors under a topic heading

Many of the brainstormed factors can and should be measured by one metric. An example might be the number of web servers, and the number of database servers. This can be joined under the single topic heading "Number of Servers Required"

Step 3 - Build the "Scoring Matrix" for each group.

The complexity in this step takes an absolute measurement and maps it to a simple 1 to 5 score. All measures should be 1 being lowest "cost, effort, time, best performance, most secure, most reliable" and 5 being the opposite direction.

(These are just very simple samples. The list and scores are completely fabricated in this picture)

Step 4 - Determine the factor weightings (what is more important than what)

I have three basic approaches for this -

  a) You just decide relative importance and allocate weightings subjectively! Great if you can get away with it, but the intention of Design for Manufacturing is to find the "best" design from a balanced set of design objectives. If we just designed software for ease of development, we may not fully consider the operational aspects and the cost of ownership over time.

  b) Paired Options (or Pairwise comparison): Get the group of people representing different domains of expertise (operations, development, business, marketing, sales) together again and have them vote A versus B, A versus C, etc. to determine what is more "important" to that person. Take an average measure of the room (more think A is more important than B). Total up the number of votes for each factor, and determine what percentage that total is of the entire selection. % weight = (count / total pairs (15) ) * 100

  c) * my preferred* Stack ranking: Get each representative from each domain specialist (operations, developers, business, storage, etc) to stack rank the factors, most important to least important. This will uncover and account for individual biases. It is my preferred method because it also allows people to say "No Impact" for a specific factor on a "perspective" of the factor. Total up the relative ascending score (assign 1 to the lowest row that was a factor, and 2 to the next one up, and so on) and determine what percentage that score is of the total points available. This will look something like this -

Consider doing this for more than one perspective. E.g. As far as Cost, how would you rank importance. As far as time to market, how would you order these factors. What you are looking for is a way to mathematically represent that one factor has a much higher impact on a desired delivery "factor". Some axis of ranking might be:

    1. Capital expenditure - Upfront cost

    2. Operational Expenditure - Ongoing costs

    3. Time to market - How quickly can it initially be developed

    4. Performance - hitting agreed service and performance levels

    5. Security - what factors make a system more secure

    6. Reliability and Stability - what factors make a system able to handle failure more gracefully)

Whatever method you employ, the outcome needs to be a table of the factors, and a weighting multiplier, E.g.

    Number of Servers Required - 24%

    Bandwidth - 20.6%

    Searches / sec - 10.3%

    Number of Deployment Items - 17.2%

    Number of Third Party Components - 13.7%

    Number of Features - 13.7%

Step 5 - Score a Scenario and Multiply By Weights

Break out excel. Use the scoring sheet from Step 3 to score a scenario. Multiply each score by the weights determined in Step 4. Total all of the weighted scores. Do this for other scenarios to compare.

In the next installment of this article series, i'll demonstrate this basic technique with some real examples and prepare a final spreadsheet template you might find useful in doing your own option analysis.

Troy.

What are factors?

Factors represent an issue, or a requirement that has an impact on the final "cost" of a product. In electronics, a "cost" will either be an increase in monetary value of building an item, or an increase in time to delivery. "Costs" in the software domain might be -

• Cost of hardware or hosting monthly fee(s)
• Increase in time to develop or deploy
• Compensating technology required for security, or risk mitigation

This isn't a complete list, but its a good start. Our ultimate goal is to define a set of "Weighted Factors" that we will use to score a particular design option. But first, lets explore the different types of Design Options, and explore a few examples in the Software engineering domain.

Key Point: Each factor varies in how linearly it will effect the "cost" value. Higher costs are bad, lower costs are good. Costs will be normalized by the weighting scale applied to each factor to ensure one factor doesn't overly control the outcome.

Types of Factors

Binary Decision Factors

Binary factors are those constraints that are an absolute Go or No-Go. Any factor that will clearly eliminate an option should be the first criteria analyzed. If a certain criteria is met (or not met), the highest cost should be assumed - ensuring that this option can never be chosen (not without due negotiation anyway!)

Tipping Point Factors

Some factors have no "cost" impact until they pass a certain threshold. An example might be disk space use. Until your product passes the requirement to need more than 100MB of disk space, there is no cost; After that you pay a premium. These factors need to place the lowest cost on a factor, once the tipping point is reached, the factor must assume the highest cost ensuring this option cannot be chosen, otherwise this factor should be zero and not impact the rest of the decision tree.

Scaled Factors

These are general quantifiable factors. The offer a mechanism to determine (and indicate) how a factor impacts cost. E.g. Adding an extra business service layer will increase the deployment complexity and may need extra servers. We'll discuss how to formulate a scale for these factors in a future article, but in this example you can imagine that adding servers has a cost, and each extra architectural layer increases the cost accordingly.

Determining the Relevant Factors

This is the crux of the story. We need to identify the factors that we will score. There is no master list of factors to draw upon. It is important that each factor fall into a category listed above - Binary, Tipping Point or Scaled.

The basic process is to get all the stakeholders into a room and extract (brainstorm) factors that will in their opinion cause an extra cost. No factor is too small at this stage (we'll filter them later), just keep the crowd focused on identifying issues that can increase/decrease effort, cost, time and risk.

By then end of a session you should have a stack of post-it notes littering a whiteboard. Use post-it notes so that you can join and link duplicate concepts and ideas. If you involve the right people, you should end up with a big list of factors. How many are too many? Impossible to quantify, but once a list of Factors is defined, the weighting process should spotlight those factors that fall below a level that will alter any outcome. These factors can then be dropped.

I've not got a complete list, or even a recommended list at the moment. Hopefully sometime in the future I'll have something more, but for the fact of this article, here are a few I jotted down in three minutes (some overlap, some are duplicate, some can't be measured, and some don't make sense at all - all problems to look at later)-

• Bandwidth utilization
• Disk space required
• Number of Architectural Layers
• Database size
• Number of Database Objects
• Number of different development languages
• Number of different technologies
• Number of integration points
• Number of external partners integration points
• Number of config settings, and ease of changing
• Production event logging, how much, to where, how often?
• Ease of deployment
• Number of Servers
• Number of third party components
• Ease we could host at a co-located facility

In future articles, we'll look at how to take this list and refine it down to a manageable set, and how we would scale and weight each factor.

Troy.

In electronics design, many elements can directly impact the cost of manufacturing a product. DfM aimed to move the tradeoff analysis for decisions affecting manufacturing as early as possible in a design phase. I'll attempt to move this into the software architecture realm in a future article, but for now I want to explain how this worked in Electronic Product design.

What design decision matter in Electronics?

In electronic product design, here are a few to start your thought process -

Component Selection - Choosing components from an approved supplier and components that meet requirements but don't exceed specification (giving latitude to safety margins) directly impact cost of an item. Assisting engineers choose preferred part, parts already purchased and in inventory, and offering alternatives can really decrease costs and improve turnaround time.

Printed Circuit Board Size and Shape - Small PCB's aren't made one at a time. They are panelized onto larger sheets, fabricated and even assembled (components positioned and soldered into place) in that form before being broken apart and put into their cases. The more individual boards you can fit to a panel, the less waste and fewer panels need to be moved through auto-assembly equipment.

Printed Circuit Board Technology - If you make the board smaller to fit a certain device, you often need to add 'layers' for interconnecting components. This adds cost; If you make individual features smaller to fit more interconnects onto fewer layers, the manufacturing yield decreases due to mis-registrations. Its a real trade-off and highly dependent on your partners capabilities.

Printed Circuit Board Hole Count and Sizes - For some PCB technologies, drilling holes can be time consuming. Smaller holes needs to be positioned more accurately and these drill bits break more often. Normally, fewer holes of larger sizes is the cheapest way to go; However, some PCB technologies don't incur a cost per hole - which one will you specify?

Component Placement - Where is it safe to put large components? Where will the battery connect? Where are the pushbuttons? All of these decisions need to be considered when the PCB is being designed - BUT they seriously impact the final case design. How can the electronics designers and the mechanical (and brand) designers collaborate to agree on an acceptable design? For extremely high volume designs, placing similar components in the same orientation can reduce the number of machine rotations and component reel changes which reduces the total time of assembly. Saving 1 minute for 1 million pieces is substantial!

Early Focus and Scoring Matrix Definition

Design for Manufacture initiatives aimed to bring focus on the types of decisions made above and allow engineers and designers to perform trade-off analysis as early as possible in the process. The product might have to be smaller than a competitors and that forces a smaller PCB size and shape, which then causes a specific choice of technology - However, the key aim was to understand that early and make informed choices about which remaining options fulfill the global good.

To build a Report Card or Scoring Matrix, the basic process is -

1. Get together with all of your partners, suppliers, fabricators and designers and brainstorm a set of issues that impact cost. Similar to the list provided above, the idea is to get the 'issues list' on the table.
2. Group these issues into a sub-set that can actually be measured and scored. E.g. "Number of boards per panel", "Number of holes smaller than 0.5mm", "Number of different components types", etc.
3. Determine relative weighting for each measurement. Some requirements cannot be broken, other just incur a cost. I'll propose a process for determining this weighting in a future article; for now, just understand they won't all have the same weighting factor.
4. Build the scoring scale for each factor. This step tries to normalize the different scales of measurements into a smaller linear set (i.e. 1 to 5, rather than 1 to 1 million for one factor, and 1 to 10 for another)
5. Calibrate the scorecard by testing on existing systems. Agree and alter the specific factor "Weightings" until you gain confidence in the scorecard
6. Use the scorecard on future design discussions.

Summary

Is it just as simple as substituting "IT Operations" for "Fabricators"; "Usability/Interactive Designers" for "Packaging Designers"; "External Hosting Partners" for "Suppliers"? 

In future articles i'll look deeper into -

• How to build a weighted score card based on issues relevant to software
• Propose some software specific issues and attempt to weight those appropriately
• Test our new scorecard and determine if it is achieving the goal we intended.

Be interested in comments as to whether other people agree there might by parity between DfM in Electronics to DfM in Software.

Troy.

I started out in the electronics engineering field, and moved into the software side of electronics design automation business shortly after that. Back in the early 1990's a lot of effort was being put into Design for Manufacturing. This was in the recognition that very small decisions made early by an isolated engineer, could have massive consequences down the road impacting costs. There were a few leaders and advocates in the field, mainly from HP and IBM at the time.

One incident recalled by Happy Holder, a HP engineer at that time was the reduction in cost of the HP Laserjet III printers. By altering the size of the main printed circuit board size by a few inches one way, they were able to double the production yield of that assembly, halving the raw material cost of the PCB. Happy Holden and IBM's Tucker Garrison at the time came up with a few simple methods for evaluating designs and allocating a report card. The most complex part of the process was getting the right people in the room to agree on the right criteria to measure, and to weight those measurements in the right way.

Manufacturing optimization comes down to improving production yield (reducing waste) and speeding up the process (reducing touch time); These principles are well known to all those proponents of Lean Manufacturing and Theory of Constraints. This book is a good start - Agile Management for Software Engineering: Applying the Theory of Constraints for Business Results (The Coad Series).

Is software yield (throughput) equivalent to DFM for Electronics "Speeding up the process"? The aforementioned books clearly describes the process of improving throughput by reducing the waste and understanding the current blocking issues. But I cannot find a process that brings focus of the cost of decisions back to the earliest possible decision point, when it is relatively simple to move many directions.

It seems obvious there is room for innovation here. Provide a framework (what DFM calls report cards) that developers and architects can use to assess possible solutions and designs for a requirement. I plan over the next few weeks to explain how the Electronics DFM process worked, and suggest a few techniques that might improve our up-front decision making process.

Troy.