The Future of Supply Chain Planning

Stephen DeAngelis

January 31, 2019

Few people would argue that lack of planning is a good thing. Benjamin Franklin once declared, “By failing to prepare, you are preparing to fail.” Do things always work out according to plan? Absolutely not. Nevertheless, I’m reminded what Dwight D. Eisenhower once observed about planning. He said, “In preparing for battle I have always found that plans are useless, but planning is indispensable.” Lora Cecere (@lcecere), founder and CEO of Supply Chain Insights, believes too many supply chain professionals have forgotten the fundamentals of planning in the digital age.  She writes, “We have lost the ability to have a discussion on the fundamentals. It drives a supply chain planning gal like me crazy.”[1] At its most fundamental level, Cecere states, supply chain planning is about managing inputs into a data model to drive outputs. The goal, she writes, “should be about the ‘success of the model output’ to drive value.”


Digital age planning is outside in


For years, Cecere has advocated outside in planning. By that she means planning must take into account all of the demand data being generated outside of corporate boundaries. Gartner analysts agree the most mature supply chain planning processes are outside in. They developed a five-stage supply chain maturity model and the most mature stages (stages 4 and 5) are outside in. According to Gartner analysts, stage 3 is the foundational maturity level “where firms coordinate their supply chain processes — shifting concentration from functional capabilities to end-to-end processing for more planning visibility across the wider chain.”[2] Outside in planning is all about the data. At stage 4 of Gartner’s maturity model, “technology tools help organizations make … more ‘complicated’ and ‘complex’ decisions. ‘End-to-end planning decisions such as an inventory strategy and optimization and S&OP trade-offs fall into this [complicated] category.’ Stage 4 SCP technology tools let companies more capably probe data and sense cause-and-effect relationships to make the right call.” Foremost among these technology tools is cognitive computing. Cecere notes cognitive computing, prescriptive analytics and machine learning are “largely making the traditional planning world obsolete.”


Stage 4 planning processes provide organizations with an extended view of their supply chains and enable profit-oriented optimization. At stage 5, organizations have a complete network view with multienterprise capabilities enabling planning and execution convergence.


Planning and decision making


Planning is all about making better business decisions. Bain analysts, Michael C. Mankins and Lori Sherer (), assert that if you can improve a company’s decision making you can dramatically improve its bottom line. They explain, “The best way to understand any company’s operations is to view them as a series of decisions.”[3] Gartner analysts discuss four kinds of decisions that must be made during the planning process. They are:


Simple decisions – “[Simple decisions are made] where the cause-and-effect relationship is known and discernable by all, including key stakeholders. … Processes and decisions that are best practices (for example, how to size an item’s safety stock level or creating a statistical demand plan based on past sales history) fit into simple decision making segment.” Simple decisions are where Cecere’s fundamentals are most clearly evident — inputs into a data model drive outputs.


Complicated decisions – “[Complicated decisions must be made when] the cause-and-effect relationship is known by a few experts but not known by the key stakeholders. The decision-making process is typically one of sensing the situation, analyzing it to get an understanding and effecting any necessary change management and then selecting the appropriate response once agreement is obtained. End-to-end planning decisions such an inventory strategy and optimization and S&OP trade-offs fall into this category. ” Clearly, the more complicated decisions become the more necessary are cognitive technologies.


Complex decisions – “[Complex decisions are] defined as a cause-and-effect relationship that is unknown by all, but potentially knowable. The decision-making in this emerging process typically goes from probing/experimenting with the environment, sensing the cause-and-effect relationship and then selecting the appropriate response. Examples here include the use of new data sources such as weather or social sentiment and their impacts on demand. Through experimentation with the new data, potential cause-and-effect relationships may be uncovered that help to enhance specific planning decisions and outcomes once relevant responses can be identified (e.g., how weather influences demand level at an SKU location level).” Complexity begs for cognitive capabilities. For example, the Enterra Supply Chain Intelligence System™ can input and analyze any number of variables to facilitate plans in minutes rather than days. Those plans can help balance and align competing corporate goals making the planning process both smart and fast.


Chaotic decisions – “[Chaotic decisions must be made when] the cause and effect is not discernable — and, as the name may imply, is in crisis-management territory. The decision-making process is typically one of acting, because no cause and effect is known, sensing what happens and adjusting and responding as appropriate. This type of planning decision tends to prevail when the decision maker has no visibility of the cause and/or effect and is just responding to a supply chain disruption of some kind and ‘hoping for the best.’ These chaotic decision types will be more prevalent when there is a lack of supply chain visibility — both internally and externally.” Obviously, no decision-maker wants to make many chaotic decisions; but, global chaos can force leaders into this uncomfortable territory. Cecere notes, “Today market turbulence abounds. Spiraling transportation costs, tariff shifts and increased expectations for customer service sparks new interest in supply chain planning. Operations complexity coupled with the rise in demand volatility increases corporate risk.”[4]


Despite emerging technologies, Cecere reports, “68% of planning happens in spreadsheets.” She also notes, “The high use of spreadsheets is an indication of a bad plan. The complexity of a supply chain precludes spreadsheet modeling.” Mankins and Sherer add, “We know from extensive research that decisions matter — a lot. Companies that make better decisions, make them faster and execute them more effectively than rivals nearly always turn in better financial performance. Not surprisingly, companies that employ advanced analytics to improve decision making and execution have the results to show for it.”


Concluding thoughts


The Scottish poet Robert Burns famously penned, “The best laid schemes o’ mice an’ men gang aft agley.” In today’s digital age, plans don’t have to go astray anywhere near as much as they did in the past thanks to cognitive technologies. That’s because cognitive systems can deal with many more variables than previously possible. No plan is perfect; but, today, supply chain planners have tools available that can make their jobs less complicated and more effective.


[1] Lora Cecere, “What Is Planning?Supply Chain Shaman, 6 March 2018.
[2] Jeff Bodenstab, “How to Attain ‘Stage 4’ Supply Chain Planning Maturity,” ToolsGroup, 7 November 2017.
[3] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.
[4] Lora Cecere, “What Value Are You Getting From Planning?Supply Chain Shaman, 21 November 2018.