Executive Briefings

Strategic S&OP Supported by Embedded Risk Management Tools & Techniques

For almost 50 years, the operations/supply chain profession has been embracing the sales and operations planning process to balance supply and demand in complex supply chain networks. As a former S&OP process owner for three Fortune 100 manufacturers, I can identify with the challenges associated with developing the process and sustaining it as well. With more and more tools emerging, especially supporting solid supply chain risk management, the future looks bright for strategic S&OP. -Gregory L. Schlegel, CPIM, CSP, Jonah, Founder, The Supply Chain Risk Management Consortium, Executive-in-Residence, Center for Supply Chain Research, Lehigh University

Strategic S&OP Supported by Embedded Risk Management Tools & Techniques

First, we need to talk about the elephant in the room. The dilemma in S&OP is that – following Gartner’s four-stage maturity model -- over the last 20 years, almost 70 percent of companies have been operating in the first two stages — Reacting and Anticipating. Why? It’s not easy to start an S&OP process and even more difficult to sustain it. The first two stages tend to be geared around getting a plan together and maintaining a regular meeting to balance supply with demand for the good of the enterprise. These two stages are totally focused on inward processes and tend to take at least four years to solidify. Then, the big jump to Stage 3 — Collaborating. This means expanding the process to your suppliers and customers. The focus changes to profitability and in Stage 4 —Orchestrating – it’s driven by demand sensing, shaping and enterprise trade-offs, including risk/reward analyses.

Needs for the next several years — The classic deterministic tools we know and love, such as time-series analysis, LP optimization, the Simplex method and others will remain; however, to handle the uncertainty, complexity and risk of our new global supply networks, we see predictive analytics, big data, probabilistic modeling and new tools such as Python, R, Hadoop, Spark and more emerging. These new tools can better handle uncertainty and effectively read and make sense of new unstructured data coming from the internet. To be successful in stages 3 & 4, we feel S&OP professionals will be better served utilizing these new tools to digitize their supply networks, run effective “what-if” scenarios to quantify how their supply chains will react to stimuli from both within the organization and outside, while evaluating unstructured data from the internet to develop statistically strong patterns associated with suppliers and customer buying habits and sentiments. Very exciting!

Then what — As more and more supply chain and S&OP professionals leverage these new tools, we feel confident that more than 30 percent of companies embracing S&OP will successfully make the jump to the “outside-in” stages, 3 and 4. We expect companies will move up the Predictive Analytics Maturity Model from Descriptive (what happened), through Predictive (what might happen next), into Prescriptive (what should I do about it) and finally to Cognitive (the system learns). With that said, the complexion of the S&OP process will change dramatically from a very structured, linear process to a more ad-hoc, event-driven environment supporting more strategic imperatives. This may involve more high-frequency/high-impact decision-making, the ability to know sooner and act faster, and accelerate the learnings across the enterprise to enhance the precision of strategic decisions.

The Outlook

Many consultancies and research organizations, including universities are profiling future S&OP processes augmented by “virtual assistants.” Think of today’s Siri, Alexa, Cortana and more, evaluating the global supply chain network overnight and providing a set of strategic and tactical “what-if” scenarios posted to your laptop, iPad and phone with extensive assumptions, corporate risk appetite rules, risk/reward trade-offs and more, waiting for your decision, while you sip your first cup of coffee. Onward!

First, we need to talk about the elephant in the room. The dilemma in S&OP is that – following Gartner’s four-stage maturity model -- over the last 20 years, almost 70 percent of companies have been operating in the first two stages — Reacting and Anticipating. Why? It’s not easy to start an S&OP process and even more difficult to sustain it. The first two stages tend to be geared around getting a plan together and maintaining a regular meeting to balance supply with demand for the good of the enterprise. These two stages are totally focused on inward processes and tend to take at least four years to solidify. Then, the big jump to Stage 3 — Collaborating. This means expanding the process to your suppliers and customers. The focus changes to profitability and in Stage 4 —Orchestrating – it’s driven by demand sensing, shaping and enterprise trade-offs, including risk/reward analyses.

Needs for the next several years — The classic deterministic tools we know and love, such as time-series analysis, LP optimization, the Simplex method and others will remain; however, to handle the uncertainty, complexity and risk of our new global supply networks, we see predictive analytics, big data, probabilistic modeling and new tools such as Python, R, Hadoop, Spark and more emerging. These new tools can better handle uncertainty and effectively read and make sense of new unstructured data coming from the internet. To be successful in stages 3 & 4, we feel S&OP professionals will be better served utilizing these new tools to digitize their supply networks, run effective “what-if” scenarios to quantify how their supply chains will react to stimuli from both within the organization and outside, while evaluating unstructured data from the internet to develop statistically strong patterns associated with suppliers and customer buying habits and sentiments. Very exciting!

Then what — As more and more supply chain and S&OP professionals leverage these new tools, we feel confident that more than 30 percent of companies embracing S&OP will successfully make the jump to the “outside-in” stages, 3 and 4. We expect companies will move up the Predictive Analytics Maturity Model from Descriptive (what happened), through Predictive (what might happen next), into Prescriptive (what should I do about it) and finally to Cognitive (the system learns). With that said, the complexion of the S&OP process will change dramatically from a very structured, linear process to a more ad-hoc, event-driven environment supporting more strategic imperatives. This may involve more high-frequency/high-impact decision-making, the ability to know sooner and act faster, and accelerate the learnings across the enterprise to enhance the precision of strategic decisions.

The Outlook

Many consultancies and research organizations, including universities are profiling future S&OP processes augmented by “virtual assistants.” Think of today’s Siri, Alexa, Cortana and more, evaluating the global supply chain network overnight and providing a set of strategic and tactical “what-if” scenarios posted to your laptop, iPad and phone with extensive assumptions, corporate risk appetite rules, risk/reward trade-offs and more, waiting for your decision, while you sip your first cup of coffee. Onward!

Strategic S&OP Supported by Embedded Risk Management Tools & Techniques