Showing posts with label Knowledge. Show all posts
Showing posts with label Knowledge. Show all posts

Thursday, January 15, 2015

The PLM-user Pitch


The PLM system pitch and the related discussions is almost always focused on the decision makers - how should you convince the management to buy, and how should you show that you provide value with your implementation?

The topic is most often focused on the disconnect between IT and Business and how to bridge the gap.

It’s of course an important topic but today we will look at it from another angle.

There is another void to fill and that is the one between the benefit of the enterprise and the actual user of the system.

Neither vendors nor the companies looking for PLM systems have (enough of) this in focus. There is a functional focus, I can agree on that, but that is not necessarily the same thing as a user oriented PLM focus. It’s more about having a checklist to see that an application can fulfill the functional requirements, which is not really the same as having the user in the center.

So what would happen if we would focus on the users? Because once bought, a system such as PLM is not only good for the business as a whole, it is also intended to help users in their everyday work.

Tools and processes for the greater good

An enterprise tool is often emphasized as the tool which should support the complete company’s need and not necessarily the individual. We focus on overall process/information improvement and harmonization and not the end-users tasks and daily work.

A company oriented pitch is also often more future oriented, than what you would like to phrase it to an end-user. The employees are more focused on the present and solving the challenges of today. That’s where our pitch should be focused – the present and what it means for the individual.

An individual productivity tool

If you take the scope of PDM, you should be able to pitch the actual idea to make it about enabling the individual; making it easier to find the right information, enabling earlier transparency as well as collaboration. For complex data sets and/or tasks it will help out in keeping data integrity, and dependencies thereby offloading the workers from otherwise tedious and error prone tasks.

But unfortunately there are challenges with this pitch:
  • The end user and the way they want a system to behave and support them in their daily work is diversified. What makes a good fit for one will not necessarily fit others. Basically I don’t believe that there is a “Heinz ketchup of PLM”, fitting all tastes. I rather believe that the need is as diverse as the salsas that you can buy in your local supermarket.
  • If we talk about PDM systems - functions associated with PDM comes with quite a heavy baggage in terms of old system behavior which has not always been perceived as enabling. A shift in technology and the ability to work more seamlessly will most likely help out in making PDM applications less of a struggle in the future.
A Tool for Knowledge

The productivity pitch will not get that much traction if your PLM system is used to “only” specify your products once you have developed them, instead of being develop within it. Unfortunately this (mis)usage is not as uncommon as you might think. In many cases putting things into the system is an administrative task at the end of what one consider value adding activities, and this really undermines the individual’s perception of having the system support her needs.

But, independent of scenario you would probably gain one thing and that is a knowledge bank. The system will create transparency which would benefit the individual, as searchable and structured information will allow for higher productivity second time around.

This transparency will also benefit the people further down the chain. The earlier you manage to accomplish it the more power you will get of it, and it’s also an opportunity for business intelligence to analyze trends earlier which again could be used as a pitch for certain end users or consumers of information.

Democratization

By sharing knowledge we will enable decentralizing and distribution of tasks. Technology will enable this. Because by systemizing knowledge we can put it in the hands of “anyone”.

Think about simulation which previously was something that only highly specialized people worked with. Today software is taken the first hit through checking the output of the individuals work before integrating it with the rest of whatever solution one is working on. All domains have it; software, hardware, mechanical design, electronics, etc. And some will take the step to create mockups which brings multiple disciplines together.

There will always be a place for specialized skills but the frontier is and will continue to move as we manage to systemize knowledge. And this should appeal to the expert as it will allow her to focus on things which are less bread and butter, at the same time as it gives the non-expert more confidence in the output she produces.

A trendy phenomena is Internet of Things; think what we can do with data collected from products in the field and once we systemize that knowledge. How will that translate into the way we design our products or conduct or service and maintenance business? Once that data is cracked it can be used as BI put into the hands of the individual.

Could this bottom-up approach result in benefits on company level (for “the greater good”)?

Could we flip this around to make it about the company, and what is best for it? Of course we could. Thinking about and addressing the needs of the individual will at the end find its way to the bottom line, resulting in better overall quality, better flows, higher productivity, higher data quality, etc.

Conclusion

IT and PLM should not be seen as a support function next to the core business – your PLM processes is actually part of your business. In many companies today it is therefore within your PLM systems that you conduct your business. If we embrace that fact, the focus can’t always be on the benefits on company level, the day-to-day work has to find its way to the PLM pitch.

Robert Wallerblad

Saturday, March 22, 2014

PLM Success – Knowledge within the operational data that you produce

This blog continues a discussion which has been the topic of two other blogs; PLM – Vision or micro-ambition? and  PLM Success - Think Inside the BoxPrevious blogs was about the importance of embracing changes and input along the way of implementing PLM and not only working blindly towards a set goal.  And the usage of your employees and cross-fertilization as a source for input.

Today we will deal with the usage of operational data as input for process improvements. 

I’m talking about the data generated while executing the company’s processes, and not “product data”. I believe that this is one of the “untapped” or at least underestimated sources for input we have, as it’s already collected to a large extent, to manage the company’s day-to-day business.

IT is traditionally a service and infrastructure provider for the business-side of the company; giving them the tools to execute their work and make well founded decisions. But, what if we could use IT to also provide the means to turn the “eye” inwards in terms of methods? Providing that a PLM system doesn’t always force a process and way of working upon you (read: not controlled in detail by the system), there is potential work to be done to see how the stipulated methods are followed. What if we analyzed how work is done and thereby receive feedback on current working methods and potential areas for improvements or alignment to reality (does it look shiny enough?).

Data warehouse analysis related to PLM processes, that I’ve seen, usually has their focus in time, money, quality and risk. Sometimes you’ll find this type of analysis in dashboard in today’s PLM systems and other enterprise systems. But they are almost always used to support the operational aspect of the business. What if we looked at the list but with method improvement focus?
  • Time – How many iterations does it take to get to a certain status in the development and what are the underlying reasons for it (communication, education, etc)?
  • Money – are we selling to the right price in the different markets? Are we able to get our “raw material” to the right price? How is our sourcing affecting transportation cost?
  • Quality – sustainable sourcing and material statistics, scrap- and recall-statistics
  • Risk – are we placing our orders “right” to get the right risk exposure? How is our in-stock volume? Could we use more low fair transportation alternatives? How good are we at forecasting and thereby being able to book, buy and commit so that we get better in-price?
With the information that we get from the data; processes and practices could be followed up to see how they are adopted and applied by business. We could also analyze good performing teams, and thereby improve company methods and best practices.

We could even take this one step further – with tools such as dynaTrace we could analyze on application level what functions are being used and how to optimize the flow and usability within the specific application in a prioritized way.

The important point here is that we could get input for the PLM journey by looking at how the company is performing and acting in its current processes. Changes doesn’t always have to be revolutionary and ground breaking, in this case they are evolutionary. Derived from the knowledge we get by analyzing data.

This is definitely not science fiction. All technology is there to be used; it’s more a question of maturity and determination to use the data with long term strategic focus and not only making the coming quarter look good.

Robert Wallerblad
www.infuseit.com