Why PLM cannot adopt Big Data now?

Why PLM cannot adopt Big Data now?


The buzz about Big Data is everywhere these days. From 2011 and up today, we can clearly see skyrocketing interest in Big Data as well as to what is behind this buzzword. Companies around the world are trying to figure out what Big Data means for them and how they can leverage it now. Engineering and manufacturing software vendors are doing this as well. I’ve been speculating about opportunity of PLM vendors to dig in Big Data last year. So far, I’ve heard lots of talks, but never seen much practical results of how Big Data can help to improve PLM products as well as influence product development processes.

I stumble on AllThingsD article – Big Data and the Soles of Your Shoes. Take 10 minutes and read the article. It speaks very nicely about modern customer-manufacturing e-commerce driven interaction. The overall process of information flow is interesting – product configuration, ordering system, materials supply, financial transactions, transportation and many other aspects. You can only imagine of how many data pieces should be moved behind this scenario – product information, bill of materials, manufacturing orders, shipment tracking, manufacturing process, delivery shipment. I specially liked the following passage coming as a conclusion of the article:

Big Data always comes across as “Big” first and “Data” second. What I urge you to do is think about the “small data.” This type of data is what happens every moment of every day. The humble pair of shoes represents small data. It’s a pair of shoes. It doesn’t pretend to be a space shuttle. But that pair of shoes has generated a massive quantity of data in its journey to you.

Small data represents the constant dripping faucet of information you generate every day. From ordering food at a restaurant to visiting a Web page to buying a pair of shoes, this faucet never stops. The amount of small data out there trumps the amount of Big Data.

The article made me think about interesting term coined by social scientists – Ambient Awareness. It refers to the information that surrounding us online – social networks, e-commerce other websites producing so-called activity streams. These streams creates business specific contextual information. The problem is that despite wide adoption of social networks in consumer spaces, organizations are still in a very premature phase of understanding how to use and leverage this information and how it might be relevant.

The challenge for most manufacturing organization is how to use right snippets of Big Data. Let’s take product design and cost assessment process. In my view, the opportunity is to see how product configurations and variety design options are impacting product cost. The pieces of data to make this analysis are in the data flow between vendors, suppliers, shipments, material cost, etc. Now think about engineer option to live in the ambient awareness of information driving towards right design for cost process. The main question that comes to my mind is related to ‘relevance’ of every bit of big data coming from outside. What is relevant to cost? What impact every bit of information has on overall cost? How to calculate it and how to put it in front of engineer at the right time?

What is my conclusion? Big data is a big opportunity for many companies. However, “big data” is too big and too abstract for companies to understand and use. Companies need to develop a way to use small bits of data coming from different sources to drive decision process and choose options. This is not simple and will not happen overnight for most of manufacturing companies using PLM systems. PLM vendors need to come with the approach how to inject small chunks of Big Data in the product development process. A task for PLM strategists and product managers. Just my thoughts…

Best, Oleg


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  • Dana Nickerson

    Oleg, I understand your point but the problems are the lack
    of knowledge and tools for designing products that can produce and use big
    data. Big data techniques have been around a long time and were pioneered by
    financial institutions 10 years ago. I heard a statistic that 70% of stock
    market trading is actually done by trading bots that use big data to calculate
    trades. These techniques will make their way into product development but the companies
    that supply tools to product development companies have to figure out how to
    make use of these techniques. When CAD and PLM was first deployed many years
    ago, industrial companies were not asking for CAD systems. These systems and design
    techniques had to be sold. A similar situation is playing out today.

    There are hundreds if not thousands of ways to use data to
    develop better products and improve the development process. The key is a data
    mindset. It is true that most industrial companies don’t have this data
    mindset. The ones that develop a data mindset will surpass the ones that don’t.
    Just as in the financial business. The good news is that financial companies
    are not sucking up all the data scientists these days. Industrial companies
    need to start hiring data scientists and putting them into their product
    development teams. And the PLM companies have to develop tools that enable big
    data based product development.

  • beyondplm

    I agree 100%. Data mindset is very important. It will take time, but industrial companies will learn how to design smart under the pressure of cost and competition.

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