Creative Hands-on Analytical Nimble Great Employees

Every business is trying to figure out life after Covid. Whatever wave they have been riding, the good, the bad, or the ugly, that wave will hit shore soon at a place that will not be the same as before. The biggest problem we are all facing is that, for both supply and demand, the level of volatility and uncertainty is still too high to even imagine all potential scenarios going forward.

Personally, the most challenging component of my thinking process is understanding the impact of the pandemic on business fundamentals. By that, I refer to basic concepts. Just to name a few:

• Pricing of products and services (is anybody feeling the tsunami of price increases in commodities?)
• Labor availability and cost (can you find people and retain them? At what cost?),
• Global supply chain capacity (how lucky are you moving freight and containers at contract rate? on time?).

These critical questions are meant to be answered in the context of the continuous “think-act” flow from Strategic planning (medium-long term) to Operational execution (short-medium term), and every company does it in its own different way. They follow a process that is naturally based on their culture and business management model, both heavily contested at this time, because of their inability to
provide successful answers.

The concern with most business management models is that they have four inherent flaws, four “sins” that permeate the organizations’ culture and DNA, flaws that can easily be observed when they behave:

• Descriptive by using only historical data to describe what happened to them in the recent or distant past with no insights into the future
• Deterministic by continuing to plan and execute based on immutable deterministic parameters that were set under different circumstances that have dramatically changed
• Sequential by executing the same script of isolated activities one department at a time
• Reactive by acting in response to a situation rather than creating or controlling their destiny

There is no way to manage a hit like COVID with this type of model.

There are no precedents to refer to (do traditional charts and regressions matter anymore?) and there is too much uncertainty and volatility in all business parameters (demand, lead times, costs, etc.). In summary, the old reactive measures that worked in the past to manage performance variation (on a
monthly basis?) do not work anymore.

But there is hope! There are new models in the digital economy and e-commerce. Models that use concepts such as big data, machine learning, business analytics, and artificial intelligence. These new models are proving to be more nimble, resilient, and effective than the traditional model.

According to Gartner: “The digital economy assumes that all customers are oriented to interacting with the business in the most convenient place for themselves and at the most appropriate time, as well as in the most convenient way. In addition, interaction with brands is carried out through experience that is unhindered, omni-channel (using different channels), direct, contextual and personalized”.

These interactions are flattening the layers between consumers, customers, manufacturers, and suppliers. A business management model that does not use all available data in this new ecosystem will always be suboptimal. There is an opportunity to connect all agents in the extended supply chain, from
suppliers’ suppliers to customers’ customers, and build business management models that are able to “sense” (trends, signals, behaviors, risks) and prescribe “responses” that maximize customer and consumer experience, driving optimal business performance.

I wanted to use these concepts to build my own future proof decision-making process and I developed a thinking framework that has become the cornerstone of my new business management model.

I focused my mission on evolving from:

• Descriptive to Predictive, by embracing the concept of “sensing and responding”
• Deterministic to Stochastic, by incorporating the complexity of variability and volatility as part of reality
• Sequential to Concurrent, by establishing multidisciplinary decision-making processes
• Reactive to Proactive, by preparing the organization and setting the pace

Some examples of how I have implemented the model so far in Sales, Operations, and Supply Chain
planning are:

• MEDIUM-LONG TERM PLANNING. Sales, Inventory, and Operations Planning (SI&OP) dynamic dashboard. Data is updated as ingested (units and dollars) for all products, categories, customers, and business units, with the ability to “sense” actuals vs. plan continuously. Data lake and algorithms connect forecast, demand, capacity, labor, container, warehouse, and financial data (revenue and margins). Full SI&OP review process running
  weekly, including financial re-forecasting.
• SHORT-MEDIUM TERM PLANNING. Integrated Business Planning (IBP) dynamic dashboard. Data is uploaded once a day. Data lake and algorithms combine all vectors of data for forecast, customer orders, inventory, point-of-sale data, production control, import flow control, financial data (revenue and margins). IBP process drives all product allocations.
• ORDER EXECUTION AND INVENTORY ALLOCATION. Data is updated in real-time for all inventory and orders. Algorithms able to “sense” changes in demand by SKU and customer and “respond” through an allocation process, dynamic re-forecasting, and dynamic inventory placement algorithm that looks at needs for the next 1-day, 3-days, 14-days by echelon.

I am sure that, in the past 12 months, there has been a tsunami of development of new business models based on better end-to-end visibility and faster and more accurate decision making. I can’t wait to see the incredible transformations that many companies have gone through to position them to deliver
amazing results in the post-covid world.

Some technical advice for all of you thinking on embracing this transformational journey:

• Use Machine Learning algorithms to find trends and signals to predict future behavior. Become predictive and prescriptive.
• Increase the frequency of decision-making meetings and involve stakeholders from all relevant departments. Work concurrently.
• Develop algorithms to reflect true variability of business parameters. Do not be deterministic, every parameter in your business has a probability attached to it.
• Communicate decisions immediately upstream to customers and downstream to internal and external suppliers. Be Proactive.

I am convinced that this new model has helped me manage through the crisis so far and will continue to serve me well going forward, but implementing this new model required some difficult transformations impacting people, process, and technology. Technical problems and process changes will be the least of your worries. Technical problems have technical solutions, and there are many structured techniques for process design. Your key to success will be people.

You need “Creative Hands-on Analytic Nimble Great Employees” 🙂

And for now, stay safe, simplify, and accelerate.