The road to more sustainability is a necessary agenda for all businesses. It involves all industries. Our society and economic life will be met with demands and expectations for thorough change to fulfil objectives with sustainability. If it is not already a reality for the businesses, it is only a matter of time before this reality affects all the boardrooms.
I believe there is a need to put innovative solutions based on new technologies into play to help with sustainability and improve society in general.
The new technologies primarily concern the use of artificial intelligence (AI) and whether it can help our businesses and society to become more sustainable.
30 percent less waste
We have developed a solution that optimises how many magazines that need to be printed and distributed to the retailers, for a media house. The solution is based on AI, an algorithm that contains large amounts of historical data. Using several built-in parameters, the algorithm can help the media house to predict how large the total circulation of a certain title has to be per week. The algorithm can also predict how many copies that need to be distributed to the different points of sale.
For instance, the challenge is that a weekly magazine loses its value the week after a new magazine is published. The unsold magazines are being incinerated, which leaves an unfortunate carbon footprint.
Our solution entails that the media house now delivers 30 % fewer magazines to incineration. It will be even better in the future. The AI embeds week by week and month by month, which means that new data can assist the media house to better predict possible sales patterns right at the individual point of the scale.
Concretely, the algorithm proposes a number for the circulation of the decision-maker, who is a human being. The decision-maker can adjust from their gut feeling or other significant factors, which the algorithm does not know anything about. However, the most important is that the prediction from the algorithm is data-driven. It does not have bias, and no human being is capable of holding as much data as the algorithm, which becomes stronger over time in line with even more data collection.
Artificial intelligence becomes a tool for optimisation and for minimising waste. In this way, the mindset can be transferred to other industries with other types of “pernicious” goods, whether it is food or other goods with a short life span.
Artificial intelligence helps against churn
To provide another example where we have made use of new technologies to achieve improvements is related to the NGOs. However, it is important to talk briefly about sustainability, where the ESG-goals involve three dimensions. The E is Environmental, which is dominant, the S is Social or Society, and the G is Governance or Responsible Management.
Regarding the social and societal dimension (S) of sustainability, we are helping two NGOs pro bono to develop an algorithm that can predict when the organisations’ contributors will be inclined to stop their donations. It enables organisations to try to save the continued donations.
The special thing about helping the NGOs is that it is a machine learning solution that is shared between two NGOs. The two organisations do not share data at any time, but their respective data enrich the algorithm and hence improve its ability to predict challenges in the organisations’ donation flows, which is vital for an NGO. The donation algorithm applies to industries that have subscription, contingent or recurring sales as a business model.
Travelling Salesman problem
We also cooperate with ServiceNow, Google and Microsoft to develop solutions to the so-called Travelling Salesman problem, which suggests visiting a given list of cities/locations using the shortest possible drive. We help to develop innovative solutions based on quantum technology. It is an example of the usage of digitalisation to help reduce carbon emissions and something that fitters and all service businesses can benefit from.
In addition, I also believe that we always must remember that solutions created from digitalisation and artificial intelligence should be drawn up sustainably. In this way, power consumption, for example, occurs at a time when there is the greatest possibility that production has taken place based on renewable sources of energy.