Retail
Artificial Intelligence Bridges the Supply Chain Gap
17 August, 2018 | Written by: Tony Morgan
Categorized: Artificial Intelligence | Retail
Share this post:
Retail and consumer products companies continue to innovate in the area of customer engagement. It’s clear they believe if they don’t do this they’ll be left behind, or possibly even disrupted out of business altogether. At the same time, we continue to see significant investment in operations, including robotics and automation in distribution centres. But when it comes to supply chain management, there appears to still be an innovation gap.
Artificial Intelligence could be the Solution
In working with a number of organisations in recent months, that’s a common concern I’ve heard. Teams recognise and value the fact that their organisation has invested in customer-facing innovation and automating aspects of the supply chain. Still, they harbour a nagging fear that the critical area of the business they work in risks being left behind.It’s great, they say, that their customers now see them as an innovative business and that their distribution centres can work so much more efficiently. But to feed our distribution centres and ultimately satisfy our customers, they say, they need to get the right orders into them at the right time.
For some organisations, this has been an area of significant under-investment. Many teams continue to find themselves lost in a fog of spreadsheets and/or multiple IT systems. As online and store deliveries become increasingly near real time, now’s a good moment to address this area. It’s one IBM has already recognised. The key, we believe, is to use the same artificial intelligence technologies we’re using to drive customer insight and engagement and apply them to the major supply chain challenges facing buyers, merchandisers and logistics teams.
An Intelligent Advisor
The new IBM Watson Supply Chain Insights solution achieves this. It continuously learns about a company’s supply chain operations and patterns of activity. It analyses and spots trends in the data from multiple systems, including information from trade partners. The objective is to enable these teams to build and operate more intelligent, demand-sensitive and customer-centric supply chains.
IBM Watson Supply Chain Insights has been designed to act as an intelligent adviser to supply chain professionals. It alerts them to potential disruptions and provides insights into estimated time delays along with the financial costs of any issues. It can even recommend relevant experts to join and work with the Watson technology in a virtual workroom, linking subject matter experts across the globe to quickly solve the problem.
Imagine, for instance, a weather event in Asia presented a threat to supplies of a key Christmas-related product. IBM Watson Supply Chain Insights could be used to predict the threat to Christmas success, identify key personnel required, invite them into a collaborative workspace and assist the team in finding an alternative supplier to provide the order.
If we can put the right technology into the hands of supply chain professionals and design it in an intuitive and easy to use way it can make a huge difference both in terms of their job satisfaction and addressing wider business KPIs, such as reducing demurrage costs, meeting customer promises to increase net promoter score and ultimately increasing sales.
Learn more about how IBM is transforming supply chains with artificial intelligence solutions.
Enterprise Business Unit Technical Leader
Reducing the time taken to write regulatory submissions – Introducing our Accelerator
The Case for Generative AI in Regulatory Acceleration Generative AI and automation are now enabling digital transformation across biopharma, allowing radical reshaping and automation of core processes – and focusing human effort where it is required. Companies embracing this approach across the whole organisation are deriving significant competitive advantage and transforming the way work is […]
Impact on Data Governance with generative AI – Part Two
Many thanks to, Dr. Roushanak Rahmat, Hywel Evans, Joe Douglas, Dr. Nicole Mather and Russ Latham for their review feedback and contributions in this paper. This blog is a continuation of the earlier one describing Data Governance and how it operates today in many businesses. In this blog, we will see how Data Governance will […]
Impact on Data Governance with Generative AI – Part One
Many thanks to, Dr. Roushanak Rahmat, Hywel Evans, Joe Douglas, Dr. Nicole Mather and Russ Latham for their review feedback and contributions in this paper. Introduction As artificial intelligence (AI) and machine learning (ML) technologies continue to transform industries and revolutionise the way we live and work, the importance of effective Data Governance cannot be […]