From laggards to leaders

Seven key trends that willredefine SCM in 2023: Insights from o9solutions.

o9 solutions, a leadingenterprise AI software platform provider for transforming planning anddecision-making, shared key insights from its supply chain experts and leadersand highlighted eight interesting trends that will redefine Supply ChainManagement (SCM) in 2023. 

Supply chains will become the strategic drivers of business

During the pandemic, companieswho had been investing in their SCM are positioned to deal with change morerapidly. Companies that are building a future strategy would need to think ofthe criteria, indicators; and, how this is a continued investment. The key isto not lock yourself into anything unless you are 100 per cent sure that thatis the direction you want to go.

Disruption can become a catalyst for supplier collaboration

One major impact that is beingwitnessed in the oil and gas industry is disruption in operations from rawmaterial shortages and delays, and headwinds brought about by inflationincreasing price of materials. Companies are getting to a point where they can’thandle additional demand and will cycle through their existing inventories.

The other big area of impact islogistics – supply gets stuck at ports, and clearance and delivery take timedue to a shortage of labour. There is also an increase in supplier collaboration.

Service levels improve when thereis a platform where suppliers can see the demand and can update their commits.In today’s constrained supply market, it is even more critical to know whatyour suppliers are able – and, unable – to support and, then, how best toallocate to high-priority demand.

Circularity could change business models

Circularity and supply chaintransparency will be critical in the fashion industry, especially as EUregulations will mandate companies to provide details about their carbonfootprint. As more consumers are becoming aware of sustainability and HR issueswithin the industry, purchasing trends may shift towards higher-qualityproducts for those who can afford them or second-hand items.

Retailers will also need to startshifting their business models to become more agile, increasing collaborationwith their network to produce limited batches but faster to meet theever-changing demand without compromising the product quality.

Circularity means a product needsto be more durable, as well as recyclable, reusable, recoverable, etc. In majormarkets such as Europe, consumers are looking for more durable, long-lastingproducts, because products that do have these characteristics become waste andgo to landfill faster.

Brand manufacturers will likelyneed to engineer their business models to accommodate a lower turnover rate ofhigher-cost, more durable products on a year-over-year basis. This willcharacterize the transition to a sustainable, circular economy.

Product environmental ‘footprinting’ will become more prevalent

Over the next three to fiveyears, industries will have to incorporate true sustainability — not simplyadhere to or comply with sustainability reporting standards. Companies willhave to transparently share metrics related to their decarbonization efforts ortheir use of non-sustainable materials in their product lines.

Historically, the product'footprinting' exercise was both tedious and expensive. Typically, product lifecycle studies included just a handful of products, and results wereextrapolated to similar products.

Currently, there is a lot ofeffort being devoted to making the product life cycle assessment process moreautomated and streamlined. The goal is to create templates allowing you togenerate product environmental footprints efficiently, thereby increasing thethroughput of the process without requiring highly specialized domainexpertise.

The proliferation of data will change the scope and role of demandforecasting

The things you buy and use to the things that you say anddo – all of this is going to become data. It is going to get bigger and bigger.

Traditionally, companies had one stream of data, which wastheir sales, shipment, or invoice history. That single stream of history wasused to indicate what you are likely to do next month and next year. Now youhave access to 1,000 to 3,000 streams of external data. In five years, thatwill be 50,000 to 100,000.

Businesses know if they do notstart (incorporating AI/ML) now, they are going to lose because they know thattheir competitors are doing it. It has become an essential activity. From arole standpoint, companies should have a demand analyst or a data scientist, ananalytical resource who can work with the data and make the machine run.

Companies must understand what internal and external datadrivers they need, where they come from, and, once you have the information,how to manage it so that it makes sense within the technology platform. So, itis a vast topic, but you cannot get machine learning to work without obtainingthat data.

Supply sensing capabilities can help businesses navigate supply chainuncertainties

The CPG industry has experiencedunprecedented disruptions since the beginning of Covid-19. Companies have beenfacing inflation, capacity constraints in logistics resulting in significantprice increases, changing consumer behaviour, and raw material shortages neverexperienced before.

These challenges are not expectedto improve in 2023 and beyond, and companies are facing a new normal ofoperating in a world of constant disruption. As a result, there is a continuedneed for companies to invest in new processes, organizational models, and newtechnologies to help manage supply chain complexities and costs, and potentiallysense disruptors before they impact the supply chain. Organizations thatanticipate and manage through disruptions will set themselves up as industryleaders.

Artificial Intelligence (AI) will continue to shape the workplace ofthe future

A key aspect of any technology, including AI, is that itshould augment human capabilities by providing computational models, powered byrelevant data, to enable fact-based and unbiased decision-making. We seeincreasing levels of automation permeate many jobs today, both in factories aswell as in the headquarters offices of many companies. The outcome of thisautomation is that companies will have access to very granular data aboutemployees, their productivity, and the ratio between value-added vs.non-value-added activities in their work patterns. Creating a newtechnology-enabled management system is, therefore, required to achievehigh-performing organizations in any industry.

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