Effective structure and use of information flow in supply chain management is often underutilized and sometimes ignored completely creating a ‘Groundhog Day’ scenario for operations and finance managers. Traditional ERP and SCM systems which are supposed to help guide product and finance flow from supplier to customer (and back) are often paired with aging email and mobile text applications, disconnected from the product and finance systems, to report and manage issues and seek updates.
Collaboration dashboards or control towers continue to evolve and find applications in improving supply chain management. Emerging technologies in AI, IoT, and Blockchain, as in other supply chain applications, can play a key role in making collaboration solutions more effective.
While much attention is being paid to automation and the application of emerging technology to operate and monitor supply chain processes, human intervention and application of knowledge and experience will continue to be the key ingredient in moving toward more efficient supply chain management. How can you merge analog and digital to move toward truly integrated business planning?
Modern collaboration tools facilitate communication for both planning and execution (e.g., Collaborative Planning, Forecasting and Replenishment (CPFR) and Vendor Managed Inventory (VMI)) to optimize cross-organizational product and finance flows. The benefits of well-run CPFR and VMI programs are well documented, but establishing these specific solutions requires design, proper tools, and operational focus. Their ultimate success is directly dependent on generating value for both parties.
A primary challenge for many organizations is that they are only in contact with customers when there is an issue with the product or service. A phone call, text, or issue log tells your customer service something is wrong, and days or weeks can pass while attempting to resolve the problem.
Establishing robust collaboration between organizations is dependent on incorporating timely information which requires a combination of technology and process. Predictive and prescriptive analytics, IoT monitoring, and machine learning for big data will drive next-generation collaboration but bridging insights from advanced technology to action for continuous improvement requires collaboration systems supporting flexible design and seamless integration.
Gartner's research “Focus on Six Capabilities to Master Supply Chain Customer Collaboration for Value Creation” on the subject concludes that “Excellence in customer collaboration is a complex journey that requires the engagement of the entire supply chain and close alignment with commercial teams”. (See the Insight and Collaboration Newsletter featuring Gartner Research to read the full research.) While the investment in time and money can be significant, the return on investment can create a unique and hard to replicate competitive advantage with your customers.
Figure 1. The Customer Collaboration Maturity Model
Source: Gartner (May 2017)
The maturity model for this journey from react mode to orchestration identifies six capabilities with stages of maturity: scope, strategy, processes, metrics, organization, and technology required. (See figure 1 ) The evolution of the maturity model, from internal measures and processes to cross-organizational, is logical enough but the maturity model does a good job capturing the key goals and scope required to successfully implement solutions.
This framework allows supply chain leaders to identify and coordinate strategic partnerships internally through stages 1-3 and externally in 3-5. The process challenges can easily be underestimated and progress difficult to track without a solid framework.
Evolution of technology supporting the maturity model ranges from stage 1 mastery of transactional efficiency (reduce manual intervention) to stage 5 use of cognitive intelligence, automation, and smart recommendations.
Most companies are entering or exiting stage 3 unless they’ve established focused collaboration projects such as CPFR or VMI previously. In stage 3, internal visibility to supply chain transactions begin to provide insights to issues that are collaborated on in near real-time and early work with customers or suppliers on these techniques are being explored.
Customer service use cases for machine learning in the form of chat and voice bots offer a glimpse into this specific advanced technology potential in supply chain collaboration. Similarly, the finance industry is actively using ML for fraud detection, regulatory compliance, and even personalization of products and services.
It’s not hard to imagine use cases in supply chain planning and execution. A 2019 article in the Harvard Business Review  reveals that, through the analysis of 400 artificial intelligence use cases, most of AI’s business uses will be in two areas: supply chain management/manufacturing and marketing and sales. The estimated accrued value to companies and their customers is greater than $4 trillion.
Oracle offers flexible and robust technology to facilitate your journey through the maturity model. Cloud-based supply chain, finance, and advanced technology products facilitate collaboration through unified user interfaces and common data models that can be applied across your supply chain or modularly adapted to fit your existing solutions.
Customers apply the Supply Chain Collaboration product for use in building the optimal collaboration environment, driving internal and external visibility, notifications and communication to support a detect, decide and execute continuous improvement workflow.
Oracle products for machine learning, Internet of Things, Intelligent Track and Trace (ITT), and advanced analytics evolve quarterly to incorporate customer best practices to accelerate innovation for all customers. Advanced data models in the cloud incorporate and merge varied data rates and types (e.g., monthly operational data and real-time machine execution data) for decision support. Early identification of problems and the reduced latency in problem resolution has a direct positive impact on inventory costs and customer service.
B2B products and services have a life cycle beyond their creation and distribution. Your customers rely on this product or service, often for years, beyond its delivery date. IoT for applications such as predictive maintenance or smart logistics not only offers suppliers insight into the state of their products in operations or transport but also opens the door for additional value-added services that may lower the total cost of ownership or supply chain management overhead for both parties.
As supply chain practitioners, we often focus on KPIs related to customer service or supply chain cost management, but collaboration solutions can be applied to a wide range of challenges. One example is sustainability. As buyers increasingly seek insight into the origin of products and their options for recycling, companies are establishing methods and processes to ensure the right information is available for customers to understand the full product life cycle, requiring supplier and end customer input and suggestions.
The point is, collaboration with customers and suppliers happens on a wide range of topics and often requires unique approaches to tie conventional solutions together. Identifying the key areas of focus between your company and its business partners is step one, followed by the use of a focused methodology and the right tools to deliver a solution that allows you to continuously improve cross organizational benefits.
Source: Gartner,“Focus on Six Capabilities to Master Supply Chain Customer Collaboration for Value Creation ”, Beth Coppinger, Chris Poole, Simon Bailey, refreshed: 20 July 2020, Published: 9 May 2017