US drive in restaurant sign

Ready-made tips for mass customisation

Image credit: Billy Blume/Dreamstime

As well as disrupting supply chains, the Covid-19 pandemic has boosted demand for many custom-printed items. Using data across every stage of operations can help manufacturers address both challenges at the same time.

We see it every day – a menu for a local takeaway, or that mug we picked up in a trade show goodie bag. Branded merchandise this is a staple of small business marketing. Becoming the design and marketing partner of choice for small businesses means constantly optimising for rock-solid reliability, predictably consistent customer experience, choice, availability, quality – and on-time delivery you can set your watch by. What does it take to get truly personalised, high-quality products into customers’ hands?

Offering hundreds of product lines that are all 100 per cent tailored to a customer's specifications is a tall order. Especially if you think of the scale and complexity of a massive marketplace distribution warehouse, then add to that products which need to be custom-made first, not just picked off the shelf. A data-driven approach is essential to achieve that. It can help fulfil unique demands in a way that is also cost-efficient and resource-smart for the business, as well as provide better forecast capabilities and increase agility.

The manufacturing landscape has never been more challenging with global disruptions such as shortages of staff and materials, delays as well as surges in prices all following the pandemic. Manufacturing and supply chain teams love a steady ship with constant volumes and solid predictability. Competitive advantage comes from how agile your organisation can be when demand fluctuates – whether it is caused by your clients suddenly reinventing their offerings during Covid-19 or spikes during busy trading periods such as Cyber Monday.

While rapidly adapting processes and keeping fulfilment promises isn’t easy, smart data and algorithmic tools can significantly alleviate the challenges posed by unpredictability. Using valuable insights is key to make sure an organisation can deliver on every order, predict raw materials, plan for equipment and staffing levels, and prevent stock outages.

At Vista, we’d already started increasing our days of supply for materials sourced from China in January 2020. When the pandemic hit, we had to adjust to a combination of urgent new products introductions, including customised face masks, and supply disruptions both from our suppliers and for our fulfillers who were all impacted by Covid.

As an example, we saw demand for lawn signs peak during the spring season when Covid was starting to have an impact all over the world. We found that customers were customising these signs for a wide range of use cases. Everything from showing their gratitude to healthcare workers to celebrating virtual graduations and of course small businesses keeping their customers informed of their latest services and offerings.

At large manufacturing facilities, many aspects of the fulfilment process happen really quickly, and analytics is how we optimise every stage. The first data-driven decision in the process should be: to identify which factory, production line or shift – even which specific piece of equipment – each component of an order should be produced on. This calls for a careful balance between speed and efficiency: should we wait for orders with similar items so we can make best use of the space on a production gang, or should we start straight away and find an acceptable degree of waste?

Because delivery offers are always getting faster, all these decisions need to be taken dynamically at speed. When managing this complexity at enormous scale, your organisation should avoid manual intervention as much as possible. Relying on human input or intervention in such a fast environment can lead to mistakes, delays and – ultimately – unnecessary costs. Instead, full automation and continuous optimisation can help address all the vital questions with minimal errors.

A team of talented data and analytics experts should be at the heart of any forward-facing organisation operating in the supply chain industry. A diverse group of analytics, tech and data science specialists will understand the significant resources required to deliver exceptional customer services and value.

When building specialist teams, it is crucial to embrace a culture of data-driven decision making and remember that data should underpin all of the processes. Manufacturing businesses should also ensure different teams such as data product, business and marketing functions are cross-functional and interconnected. A combination of small teams that feel empowered to use creativity to solve business problems and seamless data flow and interconnected KPIs between all of them can dramatically improve overall business operations.

At Vista, our teams use varied data sources (manufacturing, shipping and customer care, for example) to provide rich analytical support for all aspects of our fulfilment operations. This includes production, quality, logistics and supply chain management. When every single order is customised, it’s not just a case of getting faster, but also getting smarter too. Using data to improve agility and forecasting capabilities, avoiding manual interventions as well as building interconnected teams of specialists are important steps towards mass customisation on scale.

Roy Wildeman is data & analytics domain lead for manufacturing and supply chain at Vista.

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