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Supply Chain Digitization: Evolving A Right Framework

Digitisation is undergoing changes owing to e-commerce and consumer habits such that companies are regularly revisiting their IT plans more often. There is still a cloud over where to get started when it comes to digitisation. Though there are no certain ways of figuring out the right framework for going digital, there are certain methodologies that will help figure out digital solutions sooner.

Insights can be collected from sensors, distributed data and connected assets to gather actionable improvements through digital and analytical solutions. The idea is to shift from linear supply chains to nimble and connected networks characterised by a continuous flow of analytics and information. There are short phases that assess the value of certain digital capabilities which helps businesses to work on it for a short time and understand how far it will go. It then goes to a steering committee which takes the final call. Depending on the ones that receive a nod, their performance is assessed and investments continue. Otherwise, they pull the plug.

Another method is to build on an idea scale and see if it can win. Otherwise, a failed idea also teaches a lot, feel experts. Digital capabilities can be developed through a bottoms-up approach and not a top-down mentality. For example, an auto parts retailer thought of enhancing its standing by being a first call supplier of repair shops. In order to reach up to the customers, the retailer came up with an app that shop owners could use to see if a spare part was available and the app would also track delivery progress. With good inventory accuracy as well as digital functionality, the retailer was able to gain.

Companies need to be clear about their objectives and vision but also be flexible about certain adversities that can happen anytime.

It is time companies take the help of digital technologies like Artificial Intelligence (AI) and blockchain to sort certain supply chain issues like using blockchain for product traceability. The idea is to use appropriate technologies only after assessing the gaps in the company’s capabilities. AI can be much more effective if the future vision and goals are in place. A SWOT analysis or strengths, weaknesses, opportunities and threat analysis can help companies to assess supply chain needs. For example, a company may find gaps in sales, while another may find gaps in inventory.

With inter-departmental and cross-enterprise, technology assessment has become even more straightened out with companies being clever and clear on the areas of orchestration the company needs to work on. There are some needs under supply chain optimisation which include warehouse management systems or ERP. These processes need to have replenishment and high inventory accuracy so that predictive analysis can be done. Even a single company uses many different systems within the supply chain. For inventory in motion, having a visibility layer is helpful.

However, the real-time visibility is disrupted by data availability in multiple systems. It requires to be first collected together. For instance, the shipment details and needed updates might be in multiple systems of logistics partners or within the organisation. This is why control tower solutions that combine visibility functions with integration have gained favour. Such visibility functions should also be able to take actions and be able to deliver on time.

The key to digitisation lies in real-time accessible information through IoT or cloud-based predictive analytics. These solutions don’t need to be created but can be serviced from third-party logistics which offer supply chain strategy around shipment visibility. Thinking big can help companies to widen their vision but not at the cost of limiting the company’s efforts.

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