My last week article about How to Measure PLM? surprised me by th number of comments for pros and cons. Check LinkedIn discussion out here. It took me some time to digest and to think why some people and companies like the idea to be measured and some don’t.
The critique of measurement (or to be more precise, the difficulties of measurement) was presented by Jos Voskuil, PLM consultant. Check his blog here. Here is the passage:
…Many points to react on as I am one of the persons who explains PLM is a journey – and for sure not a process – and therefore probably not measurable. If you can be on the market with your product 2 months earlier than the competition – what is your ROI? If you want to double your revenue (because there is a market) and you cannot double the number of people – work different, be smart, learn and scale …my experience is that in a non-digital world measuring is hard to do. How do you measure enhanced collaboration, reduced time to market despite higher engineering cost, etc. The more you can measure the more you can enhance- it is a digita/transactionall mindset which we know from ERP
The count arguments came from multiple people. Here are two of my favorites. One from Helmut Rohmer:
PLM is not one process that can be measured by a single set of KPIs. More often than not PLM is not a single system but a system of systems supporting a big bunch of various processes. Deploying a PLM solution thus for the enterprise normally means to start a journey with a first step and even though there are better or not so good paths for this journey there is not an exclusive one to follow. – Each step during the PLM journey will address specific processes that can be measured and controlled. This gives orientation and prioritization for your PLM activities.
Another comment came from Martin Ohly:
I would also say you can measure PLM, or at least your own understanding of what you think PLM is and what you are attempting to achieve. I would also contend that you can also measure a journey (or at least I can measure my own journies) … like, did I arrive on time? Or did I arrive at the correct destination? Did the destination meet my expectations? Did the journey cost what I budgeted? Would I recommend the journey to others?
The discussion about measurement made me think about recent decades of web business development and how new way to solve some business problems disrupted many existing industries and solutions.
My favorite examples are coming from Google that changed the advertising business forever. Check Ken Auletta book – Googled. Today, it is the history, but just 15 years ago, it was not so obvious. Before Google, the advertising was like selling magic. If you wanted to buy ads for the super bowl, you pay $2-3M for 30 seconds. Will it work? You pay money and take your chance. The anti-Google model opinion was sound like that – this is the worst business model in the world. You know what works and what doesn’t. In the old school business model, you don’t want people to know what works and what doesn’t. When you know, you tend to charge less money from people than when you’re selling the mystique.
Another interesting book about how Google measured and calculated everything was written by Steve Arnold – Google 2.0: Calculated Predator back in 2007.
Arnold stresses that Google has been systematically building and innovating for 8 years, and founder Sergey Brin’s fingerprints—“scale, huge data sets, algorithms, efficiency, speed, massively parallel operation, and cleverness”—persist throughout Google’s patents. Google is a company built on mathematics. Google is perhaps today’s best example of a company built on calculative thinking. Characteristics of calculative thinking include efficiency and logic, not emotional reactions. An elegant proof of a theorem bundles intelligence and beauty into a construct of great beauty. Google obviously needs revenue to expand; therefore, markets with inefficiencies that can be made more efficient with Google technology are logical targets. Analog telecommunications companies, for example, become prey to Google’s more efficient technology. Like a grand master in chess, Google uses strategic feints to obtain its objective—winning the game.
So, why to measure processes? Because if you don’t, all management efforts, spending and work to introduce PLM strategy are waste of time; you don’t have control over things that matter and organizational decisions is suboptimal. Without measurement, we don’t know if there is an improvement and product lifecycle is about to reduce mistakes, streamline processes, improve quality and customer satisfaction.
Product development, manufacturing, sales, maintenance are the way manufacturing company delivers value to its customers and other stakeholders. Are we delivering value to customers in a way that impresses them and is sustainable for us? There are tons of measures about internal processes – budget tracking, policy compliance, project completion, people management, etc. Specifically, in PLM you can measure product cost deviation, ECO turnover, sales quotation, and many others. With the introduction of IoT and the movement of manufacturing companies to service-oriented business, there is an increased number of parameters to be measured and improved.
What is my conclusion? It is a time for PLM get out of old fashion guessing and strategizing and move into digital form of thinking – calculating everything. Modern digital businesses are strongly focused on the calculation and measurement of everything. Performance of websites, metrics of application usage, user experience, efficiency, AB testing of everything. Measurement of PLM related activity sounds like no brainier decision to me. Just my thoughts…
PS. I also want to set the stage to continue the conversation and talk about soft returns and cost justification for PLM software. Stay tuned…
Best, Oleg
Disclaimer: I’m co-founder and CEO of OpenBOM developing cloud-based bill of materials and inventory management tool for manufacturing companies, hardware startups, and supply chain. My opinion can be unintentionally biased.
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