7) keep innovating; this is easily translatable to manufacturing; in fact, sustainability drives innovation in manufacturing.
8) lose the crunch; Ogilvy is referring here to the image of green as Birkenstock wearing granola munchers (hence the “crunch”!) … which is not really an issue in Berkeley! It really means making green more mainstream; For manufacturing that is what this blog is all about.
9) turn eco-friendly into male ego friendly; This is Oglivy’s way of making green less “girly green” (their words … not mine!); This does not really relate to manufacturing as, for example, green machine tools are not considered less manly than conventional ones.
10) make it tangible; convert the tangible benefits of sustainable to something that can be easily visualized; manufacturing is attempting to do this all the time – from a cost, performance, impact, efficiency or effectiveness aspect.
11) make it easy to navigate; truth and transparency … easy to follow the dots; this maps directly to manufacturing and can relate to “eco-roadmaps” and similar to be discussed more in future postings.
12) tap into hedonism over altruism; help consumers see the fun on the green side of life; not sure how we can relate this; manufacturing is to many of us “fun” already – so one can suppose that green manufacturing can be “more fun”?! Let’s not push this one too far.
So now you are probably asking, how do we connect this back to big data? If one follows the above discussion about the key steps to address this massive middle as it relates to manufacturing, one can look at the ways outlined above and see some common elements needed to enable these for manufacturing – all dependent on information.
The innovation, clarity and transparency, business model/economics, institutionalization, benchmarking, etc. are all driven by data. Data on what your process or system is doing, what it is consuming or emitting, what the impact per unit process output is, what is the efficiency of conversion of resources into product, what it the efficiency of my cycle, how does one system or process compare to another doing the same thing, how does my performance match up to my competitors in the same market, company, division, or factory, and so on. All determined by data. And data flowing from machines, systems, facilities and enterprises.
So we can close this gap, at least as it relates to green manufacturing, by leveraging the tools and capabilities of big data and the a digital view of our enterprise. This is where the story picks up next time with more details and some examples.
