From speed and pricing pressures to shifts from vertical to circular models, global supply chain<\/a> strategy is in the middle of a major cost-control shift as we recover from pandemic disruptions.<\/p>\n Harnessing the power of your data is necessary to alleviate these new supply chain pain points. In this blog, we\u2019ll look at ways you can implement better data management practices to deliver more value in three areas \u2013 technology, processes and people \u2013 to deliver more value, and we\u2019ll show examples of businesses that do exactly that.<\/p>\n The common business phrase \u201cyou can’t manage what you can\u2019t measure\u201d applies best here. When you assess data capabilities, it forces you to look at your current business models and question current standings.<\/strong> Are your processes enabled to produce better data, maintain streamlined value creation and ultimately deliver well-informed, on-the-spot supply chain decisions?<\/p>\n According to Gartner research<\/a>, \u201c92 percent of supply chain leaders expect to adopt new business models within five years, but they struggle to mitigate risk due to lack of visibility, collaboration and resource sharing with trading partners.\u201d Data management<\/a> is key when it comes to today\u2019s supply chain, especially when considering insights necessary to make faster, more impactful decisions in an uncertain industry.<\/p>\n You can achieve better data management through people, technology and processes. We\u2019ll focus on these primary areas and break down ways that data management practices can play a vital role in staying ahead.<\/p>\n In the world of supply chain, the role of technology continues to grow with customer expectations. Adopting new tech like artificial intelligence and automation in process improvement<\/a> can give businesses clearer insight into data that will help optimize their supply chain.<\/strong><\/p>\n Ramping up your AI technologies will help your organization improve its current state processes and allow you to make better decisions quickly. Using machine learning can enable more accurate supply and demand planning, making forecasting clearer and easier. At a conference, the head of Demand and Supply Planning for billion-dollar vehicle manufacturer Mahindra & Mahindra<\/a> said artificial intelligence and machine learning<\/a> algorithms have increased their forecast accuracy by 10 percent and are now the cornerstone of their strategy<\/a>.<\/p>\n Of course, you must have the right data management in place to create datasets and algorithms for AI to work correctly \u2013 further proving the need to focus on optimizing data management strategies. AI can provide preventive analytics to help any organization mitigate risk. <\/strong><\/p>\n The need for improved and integrated supply chain planning and execution has become a common theme for companies of all sizes. Harnessing the power of artificial intelligence can enable more strategic planning in today\u2019s unsure environment.<\/p>\n Intelligent process automation (IPA) can make your business more agile and links to employee retention in the long term. According to an article from The Harvard Business Review<\/a>, \u201cOne U.S. health insurer, after adopting IPA across its enterprise, found it could process claims six times faster.\u201d<\/strong> IPAs are fundamental in building better data management programs as they not only increase operational productivity but they also empower people with newfound analytic capabilities (analytics and AI), allowing them more time to create value and think big picture. With the help of IPAs, employees can focus less on algorithms and more on creativity and innovation.<\/p>\n Modular process improvement using Lean Six Sigma tools can help develop practices that enable productivity, flexibility, quality and speed. In another Forbes article<\/a> about Apple assembler and consumer electronics giant Foxconn, an industry analyst cites contract manufacturing and modularization capabilities as giving them a competitive advantage. Adopting these processes has allowed Foxconn to be more flexible in times when agility is crucial.<\/strong> For example, according to the article, \u201cits production lines switched quickly in 2020 to make ventilators for hospitals during the first wave of Covid-19.\u201d<\/p>\n Adopting process improvement best practices can help organizations achieve strategy-to-execution goals by isolating process issues, improving effectiveness and delivering more value on the spot.<\/p>\n People play the main role in any business. Implementing and developing Diversity, Equity and Inclusion<\/a> (DEI) initiatives can help expand change, retain talent and enable better decision making. Gartner predicts<\/a> in 2022, metrics for DEI will become increasingly important, stating, \u201cBy 2024, 70 percent of global organizations will report metrics to track the degree to which the supply chain is delivering against corporate diversity, equity and inclusion objectives.\u201d Companies\u2019 DEI activities play a more significant role in consumer buying decisions, so reporting progress and promoting transparency in this area through data are vital.<\/strong><\/p>\n The current and future lack of visibility is forcing supply chain leaders to invest in their existing capabilities to gain fast decision-making information from their data management strategies. Organizations can take the first step towards impactful data management by focusing on their technology, processes and people<\/a>.<\/strong> Successfully managing your data in these three areas will allow you to address supply chain challenges better to , delivering not only cost-savings but also significant quality and customer service improvements.<\/p>\n\n Data Management for Supply Chain Success<\/h2>\n
1. Technology’s Role<\/h3>\n
Artificial Intelligence<\/h4>\n
Automation in Process Improvement<\/h4>\n
2. Process’s Role<\/h3>\n
3. People’s Role<\/h3>\n
Conclusion<\/h2>\n