How do you make ‘sustainability' tangible?  
The usual answer is – unsurprisingly – a ‘well, it depends’. 
Which it evidently does.
Unfortunately, good case studies are extremely rare to come across. 
Hence, when I stumbled across such a gem in one of the primary Swiss news papers, I jumped at the opportunity to summarise it for this blog.  
Could ESG reporting finally become less repetitive and tedious?
AI has the potential to transform ESG reporting by automating compliance tracking, integrating data from diverse and unstructured sources, and streamlining audit preparation. This opens up opportunities to free data and ESG experts from repetitive, tedious tasks. Yet, while AI offers promise, tight oversight remains essential to address challenges like data quality ('crap in is crap out') and system integration. 
Cotton as an attractive alternative in tsunami regions. Leading textile manufacturers promoting the cultivation of organic cotton. New technologies and methods for natural dyeing processes and recycling. And five categories of Green Fashion in Japan.  
After 10 years in the make, CETI, the European Centre for Innovative Textiles, was finally inaugurated in October 2012. The aim of the research centre is to give the textile industry a platform to research and prototype innovative textiles that can be used in sectors like: Medical, Sport & Leisure, Hygiene, and Protection sectors representing 25% of technical textile manufacturing industry; building and civil engineering that account for 10% of the production; transport making 26% of the market volume (and 15% of the market value) of technical textiles.  
If there is an area of fashion that is truly pushing the boundaries of what is technically and style-wise possible, then it is Haut Couture.
In January 2013 2 pieces among Iris van Harpenr’s 11-piece collection at Voltage show attracted the interested of fashionistas as much as product techies: The first ever wearable dresses created through a 3D printing process. 
The KISS Principle is a design principle that stems from the 1960. 
It originated in engineering and its view point is that most systems work best if they are kept simple rather than made complicated; therefore, simplicity should be a key goal in design, and unnecessary complexity should be avoided. 
But what about complex systems such as nature? 
How simple can we go before oversimplification results in incomplete, or biased data? Before absence of consideration of relevant factors inherently lead to regrettable substitutions? And before we willingly accept that there will be collateral damages to a decision, without knowing (or wanting to know) of what nature and in what order of magnitude these may be? 
One example that illustrates where this challenge may rear what is its ugly head:  upcoming Swiss political referenda on agricultural practices. 
In the fashion industry we’re very taken to ‘trend’: the colours, cuts, styles, fabrics of the next couple of seasons or so. Yet few venture to think about how their very own industry will look like in, say, 2020 or beyond. Resting the case for the importance of building scenarios of the long-term future. 
Barcodes, RFID tags, and QR codes have each introduced a new era of on-product information distribution and acquisition.
In this article I would like to look at a family of digital solution components that many brands and manufacturers will already use and be reliant on, and that – if integrated – could be leveraged to provide full-depth traceability. 
On November 12 and 13, 2013 the yearly Textile Exchange conference took place in Istanbul, Turkey.
I was invited to run a workshop on Scenario Work as one of the 'Strategy' break out session on the first day. The workshop was fully booked with 25 highly interested and active participants. In 90 challenging minutes they experienced a compressed version of a Scenario Planning workshop. 
The term ‘circular economy’ has recently been – again – converted into a buzz word. To some extent there are a couple of good reasons for that as both common sense as well as the Ellen McArthur foundation's most recent report prove. 
Computer Science and Sustainability/ESG: these two areas of expertise combine increasingly well with every passing month and year. In fact, I am tempted to say that the two worlds of sustainability and digitalisation are surprisingly similar to one another. In a number of ways – not in all, of course! – they overlap more than they differ. And mutually benefit each other. 
Both areas represent critical skill-sets for boards and senior executives in the current and upcoming decades. This is why I thought I’d take the time to reflect on the overlaps, the synergies, but no doubt also the differences.  
The key words: systems thinking, automatisation, fraud prevention and authentication, business model distruption, usability, and the Just Transition.  
Mistra Future Fashion (MFF) is a 4-year research project (2011-2015), funded by the Swedish government via Mistra, the Foundation of Strategic Environmental Research. 
MFF has a very holistic approach that has the goal of supporting the industry to re-think their business models, design and industrial processes and promote consumer behaviour change.  
Digital tools and IT systems are a great enabler for more data, more stringent channels of how to communicate what the different players in the chain do, and how they do it, over large distances and across operations and organizations.Yet – digital tools are more human than we think they are … because they, in the end, are representatives of the values and the world view of those that have built them. 
AI has the potential to transform corporate responsibility by handling data-heavy tasks like reporting or data and KPI management. It hence can contribute to helping companies 'being less bad'. However, its potential to support professionals and companies in driving real positive impact is still developing. This post introduces AI’s current potenntial in corporate responsibility and sustainability. In upcoming blog posts we'll explore specific applications: in sustainability reporting, supply chain management, and integrating financial considerations with sustainability impact. 
At Shirahime, we have worked quite extensively over the last few months on the development of fashion industry scenarios beyond the 2020 time frame, going as far as 2045.
We mentioned for example Shell as one that used this approach to suit their own goals.
Siemens' 'Future Life' video, as presented the The Crystal in London.
A much more interesting approach, and very insightful in terms of methodology, but also how tangible the results are presented, is Siemens’ work on Future Cities 
The RITE Conference's 2012 edition showed that the challenges for the industry are clear, and so are the general directions that need to be taken. But there are some marvellous and challenging mountains to climb, and they cause a notably sensation of paralysis.  
Overconsumption or ‘simply’ consumption?
Fair resource use, or resource depletion?
Fair share, equal share or acquired share of resources?
Those are questions that pop up when the Planetary Boundaries are being discussed.  
“Is Europe living within the limits of our planet?: An assessment of Europe's environmental footprints in relation to planetary boundaries”, published in April 2020 does exactly that: it evaluates and calculates the European performance for planetary boundaries by taking a consumption-based (footprint-based) perspective. This is turn is interesting as it relates environmental pressures to final demands for goods and services.
And the results are ... shall we say: a stark call to action.  
Connecting the present and the past, learning and drawing conclusions from either, is and will remain key to creating a more sustainable fashion industry. So far, learning from the past in particular - in the good and in the bad - has been chiefly neglected. A series of thoughts. 
How can AI help connect the worlds of sustainability/ESG data, and that of company financials?
ESG is typically considered a mere cost - yet: this perception stems chiefly from a lack of integration of mutually beneficial data of these two worlds. With better approaches to cost accounting, to performance analysis, as well as using predictive analysis relate to trends, legislation and asset management, the ability of AI to integrated diverse and complex data sets may precise be the pathway to shift that needle.   
In last week’s post I looked at energy companies and their trajectory relative to the Paris Climate Agenda. The insights clearly suggested a mixed picture. A clear point of how important it is to decarbonised the way we fuel our economy and global society.
But that’s unfortunately not all there is to the energy generation picture!
What few people realise: Energy generation requires water. A lot of water.
Not just in the energy generating processes, but also in the extraction of the energy source (coal in particular), and/or the making of the necessary equipment. 
Some insights ... illustrated at the example of China.  










