Unpacking the plastic problem

Robyn Hill discusses the use of data to minimise waste in the FMCG value chain

By Robyn Hill

The issue of waste management has taken on new significance in recent times, even amongst the myriad of environmental challenges clamouring for the attention of business, government, and the general public. In the past two years, a string of waste-related issues have forced their way onto the Australian policy agenda – from the introduction of container deposit schemes in a number of jurisdictions, to the phasing out of soft plastic shopping bags by the major retailers, and on to the significant difficulties posed by China’s ban on contaminated imports. The Australian government has nominated it as a significant priority and appointed a Minister for Waste Reduction and Environmental Management.

FMCG companies are responding in kind, with initiatives ranging from the welcome yet orthodox, such as the announcement by Coca-Cola that it will move its entire range of small plastic bottles to recycled materials, to more innovative solutions. Unilever, P&G, Nestle, PepsiCo and General Mills are just some of the mainstream brands who have joined Terracycle’s circular economy platform Loop in the US over the last year, with several pilots planned globally. Closer to home, Woolworths announced in late October its intention to partner with Loop in Australia from mid-2021.

The principle of Loop is that subscribed consumers return their containers at the time of delivery for new product replacement in sustainable branded packaging. If this seems familiar, you probably remember the days when items such as milk were delivered in containers that were later collected for re-use. However, logistics for a global FMCG in the 21st century are a few steps removed from that of a small dairy in the 1960s, and these schemes will take time to reach scale and widespread consumer acceptance. With 18 months until Loop becomes a reality in Australia we need to consider what other local solutions to the waste crisis are available in the interim.

Solutions in demand

Putting aside the difficult matter of what we do with it, a critical and easily missed part of the problem is the amount of waste being generated in the first place. Across the FMCG value chain, inefficiencies and failure to account for environmental factors in decision making mean that the sector uses far more non-sustainable packaging than is necessary.

For both retailer and supplier, overstocks are a significant generator of waste – a waste of resources and money, where excess supply is discounted or in some cases discarded due to poorly forecast levels of demand. A successful approach to the problem, in effect, must pre-empt consumer purchase decisions before they are made.

Quantium is already working with some clients to hone their forecasting, building deep and expertly curated data ecosystems to power AI-led decision-making processes that precisely model demand by category, product and last point of distribution. In doing so, these clients take into account the full spectrum of individual behaviour across the consumer base, and also a multitude of external factors such as weather, economic conditions and calendar events – even where these occur at irregular intervals, as is the case with many religious holidays.

These systems link together demand forecasts from across the value chain – directing optimal production planning for each SKU and co-ordinating distribution to the right part of the network at the right time. As the decision engine grows it is continuously measuring, learning and optimising its processes as the business and consumers evolve around it.

Precisely calibrated and responsive decision engines such as this will only become more important in the future. As shoppers increasingly move online and expectations around delivery in full, on time heighten, the question of right stock at the right time will move beyond a simple question of convenience to a critical factor in the value proposition. Accurate demand forecasting to pre-empt the purchase decision and position stock close to the consumer before the transaction even occurs will be vital. Given the reputational stakes involved, businesses without the ability to accurately model demand will likely err on the side of oversupply, with severe ramifications for mark-down cost and wastage, especially for perishable items.

Data-driven approaches to packaging

Looking beyond the question of how much of a product to put on a shelf, businesses also need to think carefully about how decisions are made around packaging. Demand modelling plays into this challenge by most efficiently matching consumers with the quantity of product they need in the least amount of packaging, but there are other possibilities in this space above and beyond forecasting. As the profile of plastic waste as a consumer concern in retail continues to rise, how long will it be before a retailer accounts for this externality in the algorithms that drive their range and space decisions, and markets themselves as quantitatively greener than their competition in this regard? It’s an intriguing prospect that would have real ramifications for upstream decisions made by FMCG companies, as retailers begin to favour (all other things being equal) the product with more sustainable packaging.

In the meantime, the sharp end of the wedge for waste in FMCG lies in demand forecasting, and the companies who are investing in data-driven solutions are reaping the rewards – in the time I have been at Quantium, we’ve worked with clients on waste minimisation projects that delivered ROI in two weeks.  Businesses who aren’t yet fully embracing data’s potential to tackle the waste challenge, on the other hand, risk being left behind not only on the balance sheet but on the crucial field of public opinion.

 

Quantium is a world leader in data science and artificial intelligence. Established in Australia in 2002 and now employing over 750 people, Quantium works with iconic brands in over 20 countries, partnering on their greatest challenges and unlocking transformational opportunities.

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