Catch Up!

blue-binary-code-jigsaw-puzzleThe supply chain discipline is young. As professionals in the field we are just now starting to learn from past mistakes and develop best practices. We are searching for innovative tools to help streamline processes, cut waste and increase visibility. As a group we are starting to have discussions around big data, analytics and the integration of machines that communicate and learn over time, as part of the greater internet of things (IoT).

The challenge? Software companies have not caught up with the needs of the industry.

Leading companies have been using integrated enterprise resource management (ERP) systems since the 1980s; more than 60% of all SMBs in the US are still not utilizing such platforms and their information storage is fragmented. Furthermore, those who are using these systems suffer from lack of communication between modules, and therefore remain stuck in decision making without real time information.

Organizations that have taken the leap to integrating their business management systems rarely have an easier time gaining visibility and real time information. Software companies develop solutions in silos, they do not collaborate with each other and create platforms that mimic the static vertical structures of organizations. These outdated structures fail to empower teams within organizations to make the most informed decisions. A recent study shows that there is a breakdown in communication between sales, operations and finance in more than 45% of all integrated business solutions.

There are no benefits to inventing working capital in hosted or cloud based solutions, and employee training on new platforms if he solutions are limited by design. The software and technology that will empower the supply chains of the future allows real time, seamless knowledge sharing across multiple departments and network participants. To maintain competitive advantage in a global economy where consumer’s desires are constantly changing companies must utilize consensus based collaborative forecasting and planning within their supply chain teams and networks.

To optimize supply chain decision making actors require a platform that supports collaborative and iterative simulation taking into account all constraints across the network and integration of PoS data for accurate forecasting.

Advertisement

Supply Chain Dynamics: What if… We Could Think Differently

Screen Shot 2015-11-02 at 12.54.34Supply chain innovation means taking full advantage of best of breed technology and data algorithms that empower intelligent decision-making. The exchange of information, from inside and outside the organization, must be real time, autonomous and continuous.

Previously, I shared an article with insights into the integration of advanced data analytics in supply chain planning. Last week I had the opportunity to participate in a discussion on this topic at the 13th Annual Supply Chain and Logistics Summit. I also attended presentations from Kellogg, Johnson & Johnson and Colgate Palmolive; companies recognized as leaders in supply chain innovation and part of this year’s Gartner Supply Chain Top 25 report. Each speaker mentioned the importance of real time data integration and end-to-end visibility, and gave examples of how this is currently achieved in their respective organizations.

For more than 98% of global companies, implementing a data strategy and using advanced analytics, especially within the supply chain, is a challenge. Not all companies have the talent or financial resources to undertake this type of project. Investments in data structures, analytics and employee training are costly. Knowledge gains from this information are still fragmented between functional silos and across supply chain networks, creating a lack of value and low ROI.

What if we think differently about supply chain data, network collaboration and knowledge sharing.

  1. What if we brought everyone to the planning table?

The Sales and Operations planning process (S&OP) has taken a leading role in supply chain design. S&OP is a great way to connect previously detached processes and prepare a better forecast. This process often falls short because we do invite all departments involved to the planning discussion.

In the consumer-packaged goods industry the cost of logistics accounts on average for 7% of revenues. Logistics partners and internal stakeholders are not part of the S&OP process. This creates a discrepancy in understanding the total cost to serve, and can lead to major challenges in meeting demand and preventing stock-outs at retail stores. Unforeseen trouble in the transportation and logistics network can also hurt brand image. When we involve all actors in the planning process and use data from all nodes within the network we are able to prepare more accurate forecasting models.

Speed and agility are the most important drivers in meeting customer demand. As supply chain executives we must take full advantage of all the knowledge available in the data and capitalize on our partner’s core competencies. This is the model of future intelligent supply chains.

  1. What if we removed longstanding communication barriers?

Functional, siloed organizational structures are standard. A chain of command exists in every organization, each department has specific KPIs, and actors in a supply network have individual vested interests. The ultimate goal is to drive down costs, extend payables periods to release working capital and increase gross margin, all without regard for how this affects the overall system.

This is a direct result of the lack of communication and visibility within organizational departments, and throughout the entire supply chain.

What if we used data knowledge to create an unprecedented alignment of all stakeholders, with common KPIs across the entire network?

If we did this, we could create truly agile supply chains with increased flexibility and visibility. This network could offer better response to omni-channel customer demands. We could lower overall costs and risk by incentivizing shared inventory, shared operations and gain complete chain visibility.

Ultimately, we would create real time automated information sharing networks and continuous supply chain optimization. Participating in such a system creates value for all actors; it promotes proactive policies for risk prevention and creates cognitive systems that learn over time.

  1. What if we built supply chains with end customers in mind?

A recent study from Terra Technology finds that for most companies 10% of items generate 75% of sales, and that the bottom 50% creates a long tail contributing to only 1% of sales. The costs associated with planning, producing, moving, storing, marketing and shelving all of all products affect the overall bottom line.

Only 18% of suppliers receive point of sale data from retail partners. Without SKU level data from downstream partners in the retail sector it is impossible for upstream actors to plan accordingly. Furthermore, the retail sector continues to charge upstream suppliers for these insights. New research from GT Nexus finds that around the world 81% of adults have tried to purchase a product that was out of stock at a brick and mortar store. The study also shows that this leads consumers to become dissatisfied with the brand, 1/3 of shoppers blame the retailer and 65% of them shop for the product online from a competitor.

Unlike excess inventory, we cannot measure the lost sales due to inventory stock outs. We must rethink the design of our supply chains, the sharing of knowledge within organizations and networks to gain visibility and become truly agile. Lack of collaboration is an archaic practice in supply chain management and will serve to further distinguish leaders from laggards.

If we really planned the supply chain with the end customer in mind we could significantly lessen the number of stock outs. E-commerce and click-and-collect models apply new pressures on global supply chains. We can no longer use the same fragmented processes, information and technology to meet demand and enhance customer experience.

Screen Shot 2015-11-02 at 12.58.07

The future of competition is no longer business vs. business, but supply chain vs. supply chain. We must empower our supply chains to sense system changes and adapt accordingly, while increasing collaboration within our global networks.  Our ability to think differently about managing supply chain processes will lead to the development of truly intelligent organizations.

3 Big Data Insights for the Savy Organization

Recently the World Economic Forum weighed in on the big data conversation. You can read the article here and see below 3 insights that I consider very important and relevant:

1. Big data management is tricky, and companies must understand what dupes of data they require and the supporting structures they need to reach their data goals.

2. Insights and analysis should serve as plan of action for reaching total quality management. 

3. Full buy in from C suite is vital for the success of big data endeavor because it is a huge change for staff and often requires costly infrastructure.

In conclusion: tomorrow’s leaders will have a robust big data strategy that helps them connect with their customers to deliver high quality goods and services. This strategy will be supported by an analysis powerhouse back end able to manage both structured and unstructured data sources that meet the company’s growth goals.