John Stark Associates November 30, 2015 - Vol17 #21
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|Should your PLM Vendor be Committed?
by Roger Tempest
|In UK English, "being committed" has two meanings. In this article we will ignore the idea of sending your Vendor to a medical institution because they are not of sound mind. Instead, let's consider the other meaning:-
"Should your PLM Vendor show some real commitment to the outcome of your PLM implementation?"
This question raises other questions. How much commitment should there be? Shouldn't the commitment be from both sides? And how is the commitment to be made "real"?
To examine the last question, think of your own vendor, and go back and see how much about your current implementation is specified in writing. If you look at the contract, does it specify exactly what the vendor will provide, or is it written more like a series of escape clauses?
Most PLM contracts are set up for the provision of software and services. The contract warrants that the software will function, that there will be a certain number of licenses, and that a specified number of consultancy days will be provided. This, however, is not the same as committing to the success of the solution.
|When you buy a car the dealer warrants that the car will be fit for purpose; will meet various specifications; and function as a car is normally expected to. What you do with the car - drive it on the motorway, or drive it into a lake - is not the dealer's concern.
However, PLM is different. If the PLM sales proposition were merely that it is functioning software, nobody would buy it. PLM vendors make great efforts to uncover and explain how PLM will impact the business, and try to make the picture expansive enough for the Board to approve the new project.
It therefore seems reasonable that, having painted a picture of how the business will improve with a PLM solution, the Vendor should be prepared to commit to those claims in some way.
This is not a one-sided situation. If the User expects the Vendor to commit to an outcome, the Vendor has a right to expect certain standards of performance from the User.
These ideas may be the subject of future articles. In the meantime, the first step for everyone is to blow the dust off the contract paperwork and review what it actually says.
Roger Tempest is co-founder of the PLMIG. More information about PLM Delivery is available via email@example.com.
|Is Suspect Product Data the Elephant in the Search-and-Discover Room?
by Dick Bourke
|"Inconsistent," "inaccurate" and "incomplete" all describe what we call suspect product data. For decision-making that enables engineering productivity, design tool users must be able to trust product data revealed by a search-and-discover solution (SDS).
In this article, I'll address how to resolve the suspect issue.
Enhancing the Original Concept of SDS with Findability
A user wants to narrow the options quickly to explore as few choices as possible - with full confidence and without the frustrations that could sabotage personal productivity. Users assume the data exists, but in what condition?
As I've emphasized before, an SDS tool with access to a company's PLM and ERP systems will reveal product data without regard to the quality of the data.
A key criterion for an effective system is findability. We will define this as locating exactly what's needed, not just searching and discovering multiple choices. Thus, the degree of findability is a measure of the quality of an SDS implementation.
Findability requires a viable system for classification hierarchy, attribute creation and maintenance that allows specific parametric identifying of the needed product data.
Ranges of alternatives to develop a system are open to evaluation: manual to computer-aided. A manual approach may be feasible in some situations, but computer aids are available, including those listed at the end of this article.
For development input, numerous classification systems can be tapped, such as the United Nations Standard Products and Services Code. With computer aids, data cleansing is an inherent activity in the process of creating a classification/attribute system that meets a company's specific requirements.
Evaluating and Implementing an SDS with Findability Capabilities
|Overcoming reluctance to address the issues is clearly one. The causes could be:
Another factor to consider is whether deploying an SDS can achieve the expected benefits, fully or partially. Can a company achieve optimum or only partial results from an SDS without resolving the suspect condition of product metadata that may currently exist?
Closely related are decisions that involve which activities come first: data cleansing or implementing an SDS. One viewpoint claims that SDS first will help reveal the quality and availability of correct data, hence sharpening awareness to overcome reluctance.
Certainly, there are factors with no obvious answers. These are, in other words, situational - the classic, "it depends."
Final Perspectives and Next Steps
A findability initiative will send the annoying elephant of suspect product data out of the room.
Here are three more sources of data cleansing products and services.
PLM Grid 2015
|The PLM Grid is a two-dimensional grid showing the complete scope of PLM in a typical company that develops, manufactures and supports products.
On the horizontal axis are the five phases of the product lifecycle (ideation, definition, realisation, use, and disposal). On the vertical axis are ten components (such as processes, application software and data) that the company addresses to achieve its aim of managing its products across the lifecycle.
There are many entities within each of the components. Some examples will make this clearer.
In the PLM environment, examples of metrics and Key Performance Indicators (KPIs) include Time To Market, ROI, value of the product portfolio, cost of rework, and number of patents.
Entities within "Management & Organisation" include organisational structure, strategy, education and training.
Many people develop and support a product throughout its lifecycle. Examples include product developers, product managers, marketing analysts, test engineers, machinists and disassembly workers.
The many methods to improve performance across the lifecycle include Concurrent Engineering, Design for Assembly, Early Manufacturing Involvement, Life Cycle Design, and Open Innovation.
|Facilities and equipment are used in every phase of the product lifecycle. Examples of equipment include 3D printers, 3D scanners, NC milling machines, label applicators, kilns, extruders and so on. There are also all sorts of computing and communications equipment.
PLM applications help people develop and support products. Examples include Idea Management, Robot Path Analysis, Compliance Management, NC Programming, Plastic Behaviour Analysis and CAD.
A Product Data Management (PDM) system has the primary purpose of managing all the product data created and used throughout the product lifecycle.
Product data defines and describes the product. Examples include customer requirements, part numbers, CAD geometry, design specifications, shop floor instructions, test results, label information and patent reports.
Business processes include the New Product Development, Engineering Change Management and Product Portfolio Management processes.
Last, but not least, are the product and its components.
|According to Google Scholar, as of November 27, 2015 Product Lifecycle Management: Paradigm for 21st Century Product Realisation, the most popular PLM publication, had been cited 613 times in journal articles, technical reports, books and theses.
Citing publications referenced since the previous issue of 2PLM include:
|Before Addressing PLM ....
by Scott Cleveland
|Many things happen before the actual purchase of a PLM solution. You will need to gather answers to the following questions:
Addressing them in order:
Is the problem you are attempting to solve worthy of pursuing?
During your day (week), you may have to perform some tasks that are extremely annoying. If you had a solution in place, you wouldn't have to deal with them. Can you quantify the cost of the annoyance(s)?
Now that you have uncovered the costs resulting from your problems, what are your options? And approximately how much will you need to spend to implement any of these options?
Do the benefits of the solution outweigh the costs? Can you get budget dollars for this solution? If the answer to these questions is yes, the problem/solution is worthy of pursuing.
How do you discover the available potential solutions?
If the world were perfect, what might that solution look like? The user interface is what software looks like. What do you want your users to see on their screens? How do you want them to interact? What activities will they be performing? Will the solution assist them? How do you want the 'handoff' from one user to the next to work? Will the solution help you manage your processes? Etc.
Now that you have a vision, what solutions are available to you that can deliver a solution closest to your vision? You may have to compromise, but begin your search by looking for 'your' solution.
|You should be able to get a budgetary quote from each. Do the benefits of the solution still outweigh the costs?
What information do you have to assemble in order to move toward a purchase?
Each person will have their own thought process regarding making a purchase decision. You will need to create a proposal that will address each of their concerns.
You need to create a compelling story to persuade the decision makers to move forward with the purchase. Will you need to perform a return on investment analysis? What might that look like? You might want to perform a risk assessment to support your position.
Write your proposal. You might want to ask a co-worker to review it. Then set up a meeting to present your proposal to the decision makers. Ask them for the approval to move forward.
How will you select the solution? How will you select the solution vendor?
Visit these vendors with the thought that you will narrow down to 2 or 3. With the alternatives narrowed, speak with their customers. The questions that I like the best include: What did you like about the vendors? What didn't you like about them? What would you do differently if you could start again?
Remember, you will be working with this vendor for a number of years. You will need a good relationship with them. Do you like them? Do they listen? Are they responsive?
After selecting a vendor, work with them to come up with a project plan. Have them generate a quote based on that project plan that you can use to generate a purchase order.
In summary ....
Contact me if you would like some help ....
Scott Cleveland can be contacted on +1 408-464-6387
|LinkedIn PLM Posts you may have Missed
|Some recent posts on LinkedIn:
||Nov 11, 2015 PLM and the IoT (#6): Issues with the IoT
Nov 17, 2015 PLM and the IoT (#7): Issues with IoT Projects
Nov 23, 2015 PLM and the IoT (#8): IoT Project Success Factors
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