- Rethink Project Definition. While, historically, projects were based on the definition of process “to be states” and the mapping of the “as is” to the “to be” states, in a data-driven analytics world the implementation starts with the data. The data patterns drive the process definition. The projects are small and implemented by the line-of-business teams and the progress is ongoing. There is an unknown ROI. This flies in the face of the large IT implementation that has a well-defined outcome. In analytics projects, the savings and value proposition evolves over time. It is a test-and-learn environment.
- Embrace New Data Types. New concepts shatter many other norms. The supply chain organization is hardwired to think about structured data, linear optimization and generating reports. The use of unstructured data–images, text, social, weather–is new and the path forward to use unstructured data is not clear.
- Fall in Love with Black Boxes. Similarly, the world of prescriptive and cognitive analytics is new. Linear programming and the use of traditional optimization techniques is comfortable. There is a general mistrust of “black boxes”and teams feel better when they “touch data.”
- Blow Up Excel Ghettos. Despite spending 1.7% of revenue on enterprise technology, Excel spreadsheets abound. The supply chain is often run by groups in spreadsheet ghettos. In the words of a participant on the call last week, “We have implemented SAP APO, but are stuck in intermediate Excel. How do I move past my current state?”
- Stabilize ERP Investments. New forms of supply chain analytics are largely cloud-based and are not dependent on ERP architectures. Think beyond traditional transactional approaches and embrace new forms of analytics. To get there–resources and money–you will need to stabilize ERP.
- Look and Build Beyond the Firewall. An outside-in process requires the use of channel and supplier data. This data sharing typically requires a one-to-many or a many-to-many data model found in the emerging value-network technologies like GT Nexus, Elemica, E2open, Exostar, GHX, SAP/Ariba, and SupplyOn. The problem is that these supply chain network operating models do not interoperate and there is no integration/synchronization with the networks of the 3PLs like CH Robinson or BDP International.
- Make Master Data Extinct. The traditional organization paralyzed by master data issues struggles. I find it ironic that the manufacturer and distributor companies struggle with master data issues; yet, the companies with the largest databases are the most data-driven companies (the e-commerce pure plays have no master data issues. It stems from a different data strategy using Hadoop and cognitive learning versus tight integration and moving data.) In the words of one of the manufacturing participants on the call last week, “How can we break with tradition and consider new forms of analytics when it is not an industry norm yet for our industry?”
We will be covering these topics at the Supply Chain Insights Global Summit. We hope to see you there!
Lora Cecere is the Founder of Supply Chain Insights. She is trying to redefine the industry analyst model to make it friendlier and more useful for supply chain leaders. Lora has written the books Supply Chain Metrics That Matter and Bricks Matter, and is currently working on her third book, Leadership Matters. She also actively blogs on her Supply Chain Insights website, at the Supply Chain Shaman blog, and for Forbes. When not writing or running her company, Lora is training for a triathlon, taking classes for her DBA degree in research, knitting and quilting for her new granddaughter, and doing tendu (s) and Dégagé (s) to dome her feet for pointe work at the ballet barre. Lora thinks that we are never too old to learn or to push for supply chain excellence.