Social Tagging and PLM – Can It Work Together?

March 3, 2010

You can tag almost everything these days – products on Amazon, Photos on Flikr, Facebook friends… However, would you think tagging mechanism can help you to find Part to re-use or maybe tagging will be useful to find top priority ECO or Drawing to work on today? Social tagging became very popular since the first launch of Del.ici.ous in 2003. What I want to analyze is this popular option will be beneficial and can be used for PLM systems. The ultimate problem social tagging system is trying to resolve is findability. Tagging provides an easy and simple way to organize things. You don’t need to run into complicate structures of PLM taxonomies – classes, subclasses and structures.

Social Tagging on the Web
Tagging on the web emerged as a solution for individuals to control over findability on things in the infinite collection of web resources. Tagging came as an alternative to bookmark’s organization.Tagging provided an easy and cheap way to find your resources. One of the most important characteristics of tagging is the ability to support multiple views. You can tag something as a Restaurant, but at the same time somebody else can tag it as Food and this is making a perfect sense. This ability to tag things differently is the main point of “social tagging”. You tag as you want.

Difference with Enterprise and PLM
Now, let me take the following approach to the enterprise and PLM, specifically. How the situation will be different in the enterprise organization. I can identify three major difference that potentially can prevent social tagging to become as a powerful and reliable mechanism in the enterprise: 1/Type of content; 2/People; 3/Tagging quality.

1. Content. The main difference between internet and PLM is the content. On the internet content is infinite set of information without the specific contextual mean. In case of PLM, content has a specific structure, authority and contextual meaning (task, people, etc.). The findability of resources in the enterprise need to be more precised and support specific tasks and users.

2. People. With huge popularity of social tagging on the internet, there is the only small fraction of people that successfully applies this practice in their everyday life. My guess is about 15-20% of people. What is acceptable on the Internet won’t be acceptable to the enterprise organization. You cannot provide a solution to the 20% of the people in your organization…

3. Quality and consistency. One of the main advantages of social tagging is the ability to support multiple views. However, this is also the disadvantage. The consistency of tagging and as a result, quality of tagging system can be under the level of acceptance for enterprise organization.

What is my conclusion today? Social tagging is a very interesting approach. I do think it will find they way to be used in enterprise systems and specifically in Product Lifecycle Management. However, the way to implement it probably will be different. It can include some automatic tag generation and mixed approaches to apply taxonomies together with tagging (folksonomies) on the same content. What vendors need to learn is wide acceptance of tagging solution as a very usable user experience by many customers. So, this is a point to think about…

Best, Oleg

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5 Comments | Daily PLM Think Tank, Social | Tagged: , , | Permalink
Posted by olegshilovitsky

PLM and Product Innovation

March 2, 2010

Few weeks ago, I promised to blog about PLM and Innovation. It started by the following post – “PLM vs. ERP: Don’t manage innovation“. Thank you all for great discussion since then! Now, this is a time for me to summarize and share my thoughts.

My short conclusion about Product Lifecycle Management in the context of innovation is as following. PLM is one of the ultimate systems that can enable innovation in the organization. However, I don’t see how PLM can literally manage innovation. I think about innovation as a process in the organization. The core idea behind this process is how to manage risks related to overall innovation activities. I’ll explain this using something I call “Goose Innovation Strategy”.

Goose Innovation Strategy or How To Convert Innovation to Math? Let think about innovation as a controlled multi-dimensional activity. Our interest is to get a particular outcome, which in case of product development can be considered as next product, versions or the next product features and/or improvements. Nevertheless, developing of something new is a very risky task. What we need to do when we want to  reduce a risk? We want to distribute risk into separate activities. If we develop a single golden egg, it can crack. However, if we will be investing into Goose that laying down golden eggs, our situation can be much  better. You are able to predict results. So, think about hedge fund. Distribute risks, allow to multiple people to product multiple ideas related to the product. In this case, your future might be much more secured. Some of your golden eggs will crack, nevertheless, statistically you should be ok. The bottom line – don’t invest into golden eggs, since they can crack. You better invest into Goose in your organization that laid golden eggs. Your innovation process is how to deliver a decent percent of those eggs. And this is pure math.

PLM Role in Goose Innovation Strategy
So, how PLM can help you to apply Goose Innovation Strategy? I figured out top three factors or components of that. They are belongs to Product Lifecycle Management and needs to be supported for efficient product innovation.

1- Product Data

In my view, you need data to innovate. Period. In context of PLM, this just to say – make your product data available. If you have access to the product data (people like to call it “a single point of truth”), you’ll be able to use it as one source of innovative ideas. It is always good to have a reliable source of information about how a product designed, manufactured and built – this is an endless source of innovation.

2- Product Ideas.

Product Ideas are everywhere. In your organization,  ideas are in the heads of people that bring these ideas. No ideas – no innovation. Remember ideas, capture them, analyze them. Therefore, the next effort needs to be focused on how to capture and access all ideas available in the organization. In my view, all “social” initiatives in PLM should be focused on this too.

3- Product People

People are the source of ideas. You need to have “product people” to think about how to innovate. In order to do so, they need to exchange ideas, communicate, talk, etc. 10 years ago, the only way to do so was a separate room in the building. These days multiple communication and collaboration facilities can help you. Ideas can come to you at any time. You need to keep your “recording device” and “communication device” open. PLM can keep live links between individuals in the organization and stream of product innovative ideas.

What is my conclusion today? Innovation is a controlled activity and need to be organized and managed in the organization. I don’t see PLM as a primary responsible. However, I do see PLM as one of the enablers for such innovation activity by supporting relations between product data, people and ideas.

Best, Oleg

PS. I’d like to recommend few related books. They are essential, in my view, if you want to dive into innovation.

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8 Comments | Daily PLM Think Tank, PLM and organization, PLM and Social Environment | Tagged: , | Permalink
Posted by olegshilovitsky

PLM Platforms: Retirement Or noSQL Knock-Out?

March 1, 2010

I found interesting that nobody speaks much about PLM platforms these days. It seems to me PLM vendors and service providers are focused on the more important issues, such as industry orientation, out-of-the-box functionality, SaaS and OnDemand or even by Open Source business models. However, what happens in the PLM-platform-department? Does everything is fine and well adjusted to the weather outside? Do we have enough power to move forward with all data we have these days on PLM platforms? Can we scale up in capacity? Can we support agile system development by customers? These and many other issues came to my head. However, I wanted to focus on two specific trends: Needs to manage data for the long term and noSQL trends in data management.

Long Term Product Data
This is not a very big secret. We produce more and more data on the daily basis. Product development and manufacturing companies are not exclusion from that. Bigger companies like aero-OEMs recognized this problem time ago. Their working procedures require the need to keep data for 50+ years as well as track information about each aircraft according to the serial number. Smaller manufacturers are just coming to this place. Additional weight of the regulations moves them even faster to the point where the amount of data will come to the not controlled level. There are two aspects of long term data retention in PLM – 1/3D and geometrical data; 2/non-geometrical and process-related information. I found the most interesting project in this area is prostep’s LOTAR. So, I’m looking on the progress of this activity. However, the timeline of LOTAR is seven years, which is probably okay, when we talk about 50-year data retention.

noSQL Trends
This is a not top secret. The really big guys are not running SQL these days – Google, Amazon, Facebook… All these companies developed their own data management facilities. However, despite coolness effect, the reason behind these initiatives is simple. The ugly truth is that our good friend uncle-SQL is coming to the middle-age. And even if you cannot hear voices about SQL retirement, the question about how our life can look like “after SQL” is very much acceptable. If you are not familiar with noSQL term, I’d recommend to take a look on this wikipedia article. Also, I found the following article – The noSQL movement, written by Mark Kellog on his blog as a very interesting research in this area.

PLM Platforms Data Foundation
All PDM/PLM platforms that available on the market today are relying on SQL database technology. There is no surprise – SQL is the mainstream technology in the enterprise. I can see two potential problems related to that: change management and data capacity. The first one, change management, seems as a very critical one. Customers are struggling with the level of flexibility PDM/PLM systems can provide. Solutions built on top of SQL data is sensitive to upgrades and data model changes. PLM vendors developed sophisticated systems how to manage it. However, the problem is still in place. The second one is data capacity. This problem is not uncovered in the full scope. I believe, with the future PLM implementations, there is a real chance to discover a scale-related problems.

What is my conclusion today? I think technology matters. Big boys developed alternative non-SQL data storage options. At the time when SQL-based relational database are power our PLM platforms, vendors need to think about what next. Some initial signs to think how to manage all company product lifecycle data for 50+ years are in place. There are visible interesting alternatives. However, they required future investigation by vendors.

Just my thoughts…
Best, Oleg

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7 Comments | Daily PLM Think Tank, Future Trends, Technology | Tagged: , , | Permalink
Posted by olegshilovitsky

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