PLM, Design Quality and Cost of a Product

February 9, 2010

I want to continue the topic I started yesterday about Value Engineering and discuss how PLM can be potentially used to manage cost of a product. In my view, cost is a very sensitive and complicated topic in the organization. When PLM is normally mentioned as a tool that allows us to manage and optimize product cost, in practice I see the cost topic as pretty complicated. Before discussing what practices I can apply in PLM to manage product cost, I want briefly review product cost components.

Product Cost Elements
There are quite many cost elements. I made some diagram to figure out them below. The main total product cost combined from Direct cost and Indirect cost. The major part of direct cost is material cost. Additional components of direct cost are purchased parts, labor and tooling. Indirect cost combined from Overhead, Selling Expenses, profit and discount. Direct and Indirect costs together can be presented as a product list price.

There is additional cost classification terminologies that apply to elements I just mentioned. Manufacturing cost is  combined of variable and fixed cost. Total cost combined from manufacturing cost and selling expenses. Finally, there is the selling price combined from total cost and profit.

Product Cost, Design Cost and PLM
If we will analyze all cost elements and compare it to the design cost, we can learn that design cost is insignificant in comparison to the manufacturing cost. And this is a very important observation, in my view. On one side, design cost, itself is very small. However, on the early design stages, we have a very significant impact on manufacturing and total product cost. It means that by improving design cost, we can get significant improvements and decrease product cost. It also means, that if the company is using PLM system that allows to estimate a final cost of the product on the early design stages, it can be huge benefits and can influence overall product design and manufacturing.

What is my conclusion today? I think, cost analyzes is something that should be considered as an important part of PLM system implementation. PLM has a potential to become a system to handle all cost related data and provide total cost estimation based on current design options. From what I know, such implementation happens rarely today. My hunch is that PLM implementations and technologies today are struggling to integrate systems that responsible for the cost related information – design, ERP, requirements, supply. I’d be interested to hear what are your practices in the cost management during design phase and later? Does it seem as an important issue for you?

Just my thoughts.
Best, Oleg

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Posted by olegshilovitsky

PLM and Value Engineering

February 8, 2010

This weekend I was thinking about Value Engineering and how it can be supported in Product Lifecycle Management. So, just to bring everybody on this same page – Value Engineering. Value Engineering is taking origins in General Electric in WWII and focus on systematic approach of product improvements. For me, Value Engineering is representing a very interesting problem.

The core problem of Value Engineering, as I can see it, is in the process of systematic information gathering related to product development. My short problem definition is how systematically connect product value (worth) and product costs. This is the time when I’m thinking PLM can focus on. Since PLM can connect these two in the very systematic way, it can connect “dots” of product functions in the very early design stages, manufacturing processes and consumers/end users.

So, how do you think Value Engineering is represented today in PLM. My first test is Google. Search for “Value Engineering” and PLM brings very little results. You can see them here. Your result, of course, will be local. From what I’ve seen, Aras was there in the end of the first page. However, in general, I can see, PLM is neglecting Value Engineering as a term. So, I decided to dig inside and see if does it make sense to support Value Engineering in PLM

Definition of Value Engineering
Wikipedia: Value engineering (VE) is a systematic method to improve the “value” of goods or products and services by using an examination of function. Value, as defined, is the ratio of function to cost. Value can therefore, be increased by either improving the function or reducing the cost. It is a primary tenet of value engineering that basic functions be preserved and not be reduced as a consequence of pursuing value improvements.

Value Calculation
You can calculate the value as worth of a specific product feature divided by cost of this feature development total cost. So, assuming you have all information, you can calculate the value of product you are manufacturing for your users.

Functions and Features Definition
This is something that comes very early during a product design and planning process. As every product, before you start to design it, you are facing your future customers. Based on that you can define what functions you have to put in your product. In the end of this process, you can transform your product functions into product features.

Lifecycle Cost of the Feature
When we’ve done with the initial product features definitions, we need to calculate cost of each feature. However, we need to assume total lifecycle cost including design, manufacturing, support, disposal, etc. This is a place where PLM should effectively come to play since PLM should have all lifecycle information about a product.

Worth of the feature
The most important point. You need to estimate what is the worth of each feature for customer. However, it is not a simple task. You can use historical information, get an online survey, use any other information. I have to say, that when you live in Google-era, you may have lots of alternatives to get this information than when you had before. Of course, it depends on the type of products you manufacture. You may check QFD (Quality Function Development) methodologies. I found it very practical approach. As soon as you have done with worth of the features, just go and get a balanced view of your product value.

PLM Benefits
What I think, can be ultimate PLM benefits. If you have successfully deployed PLM system, you have a good chance to have lots of information you need already in your system. If your PLM covers requirements, you need to have a functional breakdown. If you PLM is linked to manufacturing, you have a good chance for costing information to be available.

PLM Challenges
The biggest challenge, is that PLM integration with the rest of the company is somewhat that not happening in all organizations. Most of PLM systems are still focused on engineering processes and connected well to customer’s, sales, marketing and, even, manufacturing functions. However, by focusing on value engineering, we can provide additional “values” to get things done in PLM way.

What is my conclusion today? Value Engineering has obvious values and benefits for the organization. However, ability of PLM systems to manage all information is critical. What is very important is to have cost information inside of PLM. Value Engineering approach can be, in my view, used as one of the PLM strategies in the organization to solve real problems.

Just my thoughts…
Best, Oleg

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Posted by olegshilovitsky

Why Do We Need PLM to Control Product Cost?

December 22, 2009

I’d like to continue discussing topics that create maximum confusion between PLM marketing and reality. Today, I want to talk about one, that probably in the top list of all manufacturers – product cost. Yes, you want it down, no doubt. If you will talk to PLM marketers, they will all tell – PLM is the way to go. However, how magically it will happen? Why PLM can help you manage cost? How practically it will happen? I decided to discover the potential answers on these questions today…

Let me think about a traditional manufacturing environment that is not going to implement “PLM strategies”, but indeed is looking how to decrease cost of their products. The most reasonable approach is to ask different business units to develop their cost saving programs- R&D, Manufacturing, Supply Chain, Support. I believe, these organizations will be able to deliver decent results. Now, depends on manufacturing type, they have various chances to be successful. For the long run, the company manufacturing the same (or similar) products will be able to optimize cost of products. Their best chance to do so, will be for mass-manufacturing products. Within the time, all functional areas will be optimized and learn from the experience how to manage product costs for what they are doing. There are two potential problems in this approach. First is the time scale and the second production volume. What does it mean?

Time Scale in Manufacturing
With a significant time period, your manufacturing organization has a good chance to develop reasonable good product cost practices. Designers will find optimal solutions, right suppliers will be designated and subcontracted, manufacturing facilities will be optimized, etc.

Production Volume
The previous assumption of time scale will be working if you will continue to manufacture big series of products. With growing number of manufactured items, your product cost will go down.

What is the problem with such assumptions? The only one, in my view. This is less and less happening in modern manufacturing. Market demanding customization in production and due to that time and product volume is going down. So, manufacturers need to manage very flexible practices in their environment to maintain balance between production volume, time and cost.

Now, I want to get to my original question. How PLM can help? PLM is managing product data and processes. How product cost will be resulted from that? My answer – PLM need to facilitate cross-functional IT functions in the organization. Your functional domains are separate. Most of the systems in today’s IT are department oriented and rarely have global organizational exposure.  PLM need to make a success in cross-functional data and processes management. This will be a key for PLM success in the organization. And this is still not happenings…

What do you think about that?
Best, Oleg

9 Comments | Daily PLM Think Tank, PLM and organization, PLM Basics | Tagged: , , , | Permalink
Posted by olegshilovitsky

3 main factors of mainstream PLM adoption

July 27, 2009

plm-mainstreamI had chance to discuss PLM adoption rate already several time. I think, adoption rate, is one of the factors why Product Lifecycle Management is not coming to mainstream and remains something exclusive. If I look back in the computer and CAD industry history, the revolutions happened when sophisticated technologies were moved from exclusive and more expensive environment to mainstream. Microsoft did it for PC, John Walker and his partners moved from exclusive CAD workstations to mainstream PC in 1982, SolidWorks took all experience Pro-E developed until 1995 and revolutionized it on Windows platform.

So, what I had in my mind over this weekend is to think more about how to find roots for expensive and complicated PLM implementations. What those factors that make them so complicated and maybe to put few initial thoughts about how to move them to mainstream. I thought about every PLM implementation I had chance to touch and came to a conclusion that the following three major factors or steps are always causing complexity and cost: 1/Customization; 2/Legacy data; 3/Integration with ERP and other systems.

#1 – Customization.
This is a very significant piece of every PLM implementation. I hardly believe in “typical manufacturing environment”. Yes, definitely, there is some general similarity based on industry or organization type, but fundamentally people are running manufacturing differently, have their own environment, semantics of data, customized name schemas etc. So, cost to customize PLM system to get it to the right level is quite significant. To have right customization tools and integrated programming environment is key to success here. Everything is possible in software – we know that. However, what will be cost of these “possibilities”?

#2 – Legacy Data
In order to run your manufacturing environment, you need to have “your data” in the system. Without this, you are not actually running your manufacturing with PLM. To get legacy data in the system is a very painful task, in my view. I have almost never seen this happened easy. This is almost every time set of complicated steps of exporting and importing data. Since, there is no standard data, we back partially to factor #1 (customization) again.

#2 – Integration with ERP
This is last, but not least. The first chain in product development PLM needs to support is integration with ERP. If you don’t have integration with ERP implemented, you have closed environment that almost cannot optimize your manufacturing. Most of the product cost driving factors these days are on the intersection of product requirements, design and manufacturing and supply chain capabilities. To make integration with ERP is #1 task for PLM.

So, what is my short conclusion? These three factors can move every PLM implementation to nightmare. In today’s modern PLM systems, I had chance to follow few possible solutions to resolve these issues. Most PLM providers these days are focusing on industries, verticals and best practices. Not bad step in my view. As much closer you will come to final environment, less time you will spend to customize final environment. From integration and customization standpoint, moving to Microsoft development environment, Visual Basic and script based customization can be very efficient to decrease cost of implementation.
Even if I don’t think, these solutions are completely successful, but they definitely can bring some pain relief. However, I do believe, the right solutions are probably still in the future.

I’m looking forward to your comment and thoughts. I’d be glad to learn about your experience.
Best, Oleg.

28 Comments | Daily PLM Think Tank, PLM and organization, PLM Implementation | Tagged: , , , | Permalink
Posted by olegshilovitsky

Use Predictive Modeling to Decrease Product Cost during Product Design and Development?

January 28, 2009

We are all concerned about how to decrease product cost. This is a top priority of users in today’s economic situation. But it was also a priority before 2008/9. Our primary goal is to provide systems that allows control over the cost of products. Since 80% of product cost is already defined at the stage of design and early product development, predicting cost, in my opinion, should be on the short list of PLM product developers and implementers.

 “Predictive modeling is the process by which a model is created or chosen to try to best predict the probability of an outcome” (Wikipedia).  Sounds complex, right? But predictive modeling technologies based on statistical data analyses are widely used today. Many systems analyze historical data and predict future behavior. A similar example of predictive modeling usage in PLM systems is evident in Customer Relation Management (CRM) Systems are analyzing customer level models to predict customer behavior in the future. For example, health care systems analyze existing customers to predict high-risk members; telecom operators use predictive analyses for cross-sell opportunities (by analyzing product combination patterns purchased by other customers), as well as customer churn. 

Now, how do you implement this? In my view, this is all about connectivity between your systems. Today’s design and engineering are very localized and have a limited view on what is going on outside, how customers uses their products, what happens with service departments, etc. If systems are to establish a connection between particular design decision and customer defect reports, extra expenses by suppliers etc., this information can be potentially reused to predict future cost and product defects. Even if it sounds ahead of its time, I’m pretty sure our future is there. More practical examples of predictive engineering are in the areas of FEA and other engineering analyzes. Accumulating statistical data in this area can provide good prediction results for product design connected to customer experience.

 I’d be glad to discuss with you potential scenarios of predictive modeling usage and… may be you already have some of them implemented… who knows?

 

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