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Big Data & Supply Chains Big Data & Supply Chains JLL EMEA Industrial & Logistics A logistics revolution in the making? 2018 Big Data and Supply Chains 3 Introduction Good logistics and supply chain management are about In this short paper we consider some of the specific delivering superior customer service at a lower cost, but, in opportunities for big data to make supply chains more many respects, these twin objectives have become more efficient and reduce costs, assuming businesses can challenging as supply chains have become increasingly overcome all the obstacles to incorporating big data into complex and customers more demanding. Today, supply their operations. These initial observations are based on chains often extend across the globe and involve multiple supply chains staying much as they are now but becoming parties, while customers (whether businesses or end more closely integrated with enhanced transparency. consumers) want things quicker than ever before. In addition, we discuss the role big data could play over the Over time supply chains have become better integrated as longer-term in a far more radical overhaul of logistics and businesses have joined up their internal logistics operations supply chains, by potentially facilitating a more open supply and better aligned their logistics processes with their supply chain system (or systems) in which freight is moved in ‘smart’ chain partners. However, despite this, many supply chains containers through networks of ‘smart’ open access logistics still lack transparency. In particular, the visibility of end centres and hubs. This concept of a ‘Physical Internet’ is consumer demand and the movement and precise location designed to improve the efficiency and sustainability of the of materials, parts and goods along supply chains is often global logistics system.1 However, if it is to become a reality limited for many supply chain parties. in the future it requires numerous barriers to be overcome by a host of innovations. Big data is generally defined to refer to the vast amounts of structured and unstructured data available to businesses and other organisations and typically includes the advanced analytical processing capabilities that enable insights to be derived from this data. It has the potential to substantially improve the transparency of supply chains The visibility of end and, by doing so, make them more efficient and reduce consumer demand and the costs. However, this is much easier said than done. Indeed, movement and precise location without an appropriate data strategy and information of materials, parts and goods processing and analytical capabilities, businesses may along supply chains is often simply be swamped by massive amounts of data without limited for many supply securing any efficiency or cost benefits. chain parties. 1 ‘Physical Internet’ vision has been developed by Professor Benoit Montreuil of Georgia Tech. Big Data and Supply Chains Six specific big data opportunities in supply chains There are numerous opportunities for big data in supply chains, but many of these are to do with improving supply chain transparency. In short, because traditionally it has been very of ‘substituting information for inventory’ which difficult for businesses to estimate or forecast has been highlighted in academic texts for 30 demand accurately they have had to hold years or more, but which has proved stubbornly additional inventory as a buffer against this difficult to implement.2 Big data has the potential uncertainty. Therefore, all along supply chains, to improve transparency in this way and, businesses – such as retailers or their suppliers therefore, could enable significant reductions – hold additional inventory because they do not in inventory. However, inventory cannot be know what their customers will demand. eliminated from supply chains because in nearly all cases the supply lead time is longer than However, if data on end consumer demand the demand lead time and goods are typically can be better captured and analysed and if this sourced and consumed in different geographies. information can be shared along the supply chain to give a more accurate and timely picture of demand, then each party could reduce the amount of inventory it holds. This is the concept 2 For example, substituting information for inventory is discussed by Martin Christopher in Logistics and Supply Chain Management, second edition, 1998 page 263. 5 The digital transformation of supply chains Big data can enhance supply chain performance and reduce costs Generated Internet data Structured Analytical Decision and and processing optimisation unstructured capabilities data Big data 1. Demand forecasting Static data e.g. Artificial intelligence 2. Visibility of supply Data saved from with the implementation the past of machine learning 3. Network planning 4. Transport operations 5. Risk mitigation 6. Smart warehouses Dynamic data Data created continuously and in real time Creation Stock Analysis Use of data of data of data of data Internet Big Data and Supply Chains 7 1. Better demand forecasting 4. Improving transport operations The most obvious specific opportunity for big data is where it Big data has a clear role to play in improving the efficiency can enhance forecasts of end consumer demand, by enhanced and the reducing the cost of transport operations, especially predictive demand analytics. For example, if retailers are in the final or last-mile delivery involving multiple drops. better able to utilise data on spending, together with other These deliveries are much more costly than primary data that may affect short-term future spending, such as the ‘inbound’ deliveries to warehouses and over the past 10 years weather, they ought to be able to make their supply chains or so have risen up the agenda of many businesses because more agile and responsive, by delivering an improved service of the growth of e-commerce. Big data could improve the to customers at a lower cost, see Otto case study. scheduling and routing of deliveries by factoring in dynamic data, such as real-time traffic incidents or congestion, see Ocado case study. 2. Enhanced visibility of supply Related to enhanced demand analytics is the potential of big data to improve the transparency of supply by better tracking 5. Risk mitigation and tracing products in the supply chain. The ability to track Big data could help mitigate supply chain risks. Risk and trace the movement of supplies and goods through supply mitigation has shot up corporate agendas over recent years chains has improved significantly over recent years because of following the Japanese tsunami and the flooding in Thailand the wider use of technologies but big data could reinforce this in 2011, which proved hugely disruptive for certain supply trend, with in the Internet of Things (IoT) often considered as chains. Since, then many companies have sought to get a providing the next generation of track and trace. better handle on their global supply chains including using big data to monitor events – such as the weather or potential industrial action – that could affect their suppliers. 3. Better network planning and design If big data can provide an enhanced picture of current and future demand and how supply chains operate in seeking to 6. Smart warehouses match supply with demand, then it could improve network Finally, big data has the potential to improve the efficiency planning and design. Typically, businesses undertake and reduce the cost of warehouse operations including periodic reviews of their distribution networks to ensure they by making warehouses ‘smart’. Clearly many warehouses remain fit for purpose and may seek to adapt these in line already operate with high levels of information and with expectations of growth or change. However, often these communications technology (ICT), such as Warehouse network optimisation exercises are undertaken with very Management Systems, but ‘smart’ facilities will be more incomplete data and very limited insight into possible future widely connected (including via the Internet of Things and changes. The availability of big data could plug these gaps sensors) and transmit data which could enhance both particularly via insights into potential future demand trends. warehouse operations as well as the overall performance of This would make network planning more robust and ought to the building, such as its energy consumption. help make outcomes more ‘future proof’. Big Data and Supply Chains Otto Germany German online retailer Otto together with Blue Yonder, a leading provider of artificial intelligence (AI) solutions in retail, has developed an algorithm that calculates how its customers’ purchasing habits change on a day-to-day basis. The algorithm analyses as much information as possible including historic sales data, prices, discounts, short and longer term weather forecasts and other factors that influence sales for every item in Otto’s range. This helps Otto decide which products need to be ordered from its suppliers and in what quantities and enables the retailer to have items in stock before the customer orders them. With more accurate sales forecasts, Otto can avoid having quantities of items left over at the end of the season. Otto’s artificial intelligence system works independently and automatically. It takes on tasks previously Ocado carried out by people because it is faster UK and more efficient. Ocado, a UK online grocer and technology provider, has developed a routing software which uses big data to create
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