Just over the horizon are events that will trigger great business opportunities or severe consequences. Whether on a local, national, or international scale, activities such as tariffs, regulation or policy changes, political elections, climate disasters, and more will have a tremendous impact. And while this is true for any business or industry, manufacturers are especially vulnerable. Even indirect or seemingly insignificant events can spark sudden supply chain disruptions, lost production, high operational costs, an inability to fulfill contracts, and other consequences.
The key is to anticipate, create, and quantifiably evaluate multiple options.
Disaster or opportunity?
Impending or unexpected threats aren’t all bad news. Those who adjust their sails can navigate to minimize losses or even ride the winds prosperously. As Dan Meyer, President & CEO of Campfire Interactive, Inc. explained, successfully weathering such turbulence provides a distinct advantage.
“The business world is bursting with what if scenarios. What if elections go a certain way? What if certain regulations are suddenly expanded or eased? What if we don’t get that contract? What if that hurricane threatens our southern plant? The truth is business as usual is a rare occurrence for any manufacturer. One needs to look back no further than the 2020 pandemic to understand that companies must plan for a variety of situations. Accurately forecasting the impact of events along with the agility to pivot quickly and decisively not only mitigates loss – but is proving to be a competitive advantage.”
In a Harvard Business Review article “Why Some Companies Thrived During the Pandemic,” consultant Keith Ferrazzi echoes the importance of adaptability. He emphasizes a proactive leadership approach that anticipates future challenges and continuously evolves. The article points out that those who thrived during the pandemic shared the ability to quickly and effectively adapt to unforeseen challenges through insightful decision-making. This meant quickly modifying strategies, embracing new technologies, and reconfiguring operations to face threats or meet changing demands.
Reading the tea leaves
There are several common approaches used for both immediate planning and long-term strategies. Information derived from these methods helps to set expectations, budgets, production targets, and staffing requirements while preparing for business challenges.
Time Series Analysis predicts future business performance based on historical data patterns. By analyzing trends, seasonality, and cyclic behaviors in data, companies can forecast future sales, demand, or financial metrics. While time series analysis is helpful in stable environments it struggles with sudden disruptions or unforeseen changes.
The Delphi Method gathers insights from a panel of experts to predict future events or trends. Independent forecasts are aggregated and iterated upon until a consensus is reached. While this approach is valuable in subjective or uncertain domains, it relies heavily on the quality and expertise of the panel.
Regression Analysis models quantify relationships between variables and forecast future outcomes by analyzing how independent variables affect dependent ones. This highly mathematical method works best when there are established causal relationships. However, it has limitations in predicting events where relationships between variables change over time.
Market Research and Surveys provide direct feedback from customers, partners, or stakeholders to make predictions about product success, customer demand, or market shifts. While this qualitative approach can provide valuable insights, it may lack accuracy if respondents fail to provide reliable or representative data.
While insights gained from such methods provide the framework to forecast growth while developing contingency, none can offer reliable answers in the face of shifting variables. For this reason, a growing number of manufacturers are adopting a more dynamic approach.
Scenario modelling
Unlike other planning methods, scenario modeling embraces uncertainty acknowledging that the future is not fixed. As a strategic management tool, it is used for proactive problem-solving, fostering resilience by addressing uncertainties.
Scenario modeling combines both qualitative and quantitative approaches, offering flexibility to adapt to rapidly changing environments. This empowers stakeholders to test and measure the financial ramifications of the alternatives and draw data-driven conclusions to confidently navigate, or leverage, the threat or opportunity. Because reliable insight comes from identifying and measuring the effects of various what ifs, it’s important to create and compare multiple iterations. And scenario modeling does just that allowing plans to be continually evaluated and refined as situations change or progress.
Solutions developed by Campfire Interactive, Inc. help manufacturers identify, plan, develop, and execute their product portfolios. The company’s software suite includes opportunity management, sales forecasting, market share management, cost and price estimation, change cost management, and project portfolio management. And in the wake of business uncertainty more manufacturers are employing the software to financially quantify the impact of events.
So, what makes scenario modeling a dynamic approach? For one Tier 1 automotive supplier, Campfire software allows them to blend customer releases to the plants against order volumes, vehicle inventories, and vehicle sales. This is especially beneficial in balancing procurement and production with inadequate sales projections and vulnerable supply lines.
“Today some automotive OEMs have stopped reporting sales monthly, consequently we only have access to quarterly sales data; and things can change dramatically between these reports.” said a senior executive for the manufacturer. “On top of this, inventory data can be delayed. Unlike the consumer markets where we get instant feedback on what’s moving, sales are extremely difficult to model in the automotive supplier business. When you consider that we must order components from sub-suppliers with 90 to 180-day lead times, you can understand our challenges and why we must be prepared to pivot quickly.”
Campfire’s software is increasingly used to model the financial impact of a widening variety of events across the extended enterprise. Some of these applications include:
Elections
Election results can make-or-break a manufacturer. This is true at all levels from national and statewide races to those held locally as incoming administrations are generally anticipated to impose, modify, or eliminate mandates, regulations, and taxes. Consequently, manufacturers must constantly scrutinize potential outcomes, model the effects of these possibilities, test and re-test contingency plans so that they can react quickly.
To add to the complexity, things aren’t always going to go as anticipated. The senior executive explained that while 2025 will undoubtedly bring changes, it doesn’t necessarily mean that they will all be as expected. He cited the electric vehicle initiative as an example.
“Onder the Trump administration some fully expect the elimination or rollback of electrification mandates and incentives,” he said. “But not so fast. While it’s a popular belief that under a Trump administration EPA targets are likely to be eased or even dropped, as manufacturers our future relies on accounting for all possible outcomes. That said, we must anticipate that ICE vehicles will be continued and at higher volumes while the BEV vehicles that might have replaced them under different circumstances are delayed.
The former may give good revenue, but the latter means that the large investments the OEMs forced us to make would not be covered. Scenario modeling aids us in layering in what types of vehicles might sell or be produced in the coming months.”
Even today, EV mandates are continually being pushed back. And in some countries, these vehicles simply aren’t selling as expected. Hamstrung with hefty investments in tooling and added labor, automotive manufacturers are being forced to evaluate the options in preparation for some difficult decisions.
“What happens if BEV sales targets aren’t met; how will this impact our production and profitability? China, for example, has more than 400 BEV models available, yet 90% fail to sell more than 10,000 a month. This is well below the volume needed to sustain manufacturers. So, what happens if that number rises, falls, or remains flat? How is business impacted in the near and long-term? Now throw hybrids, tariffs, and trade wars into the equation and things get even more uncertain.”
Labour
Tied closely to the renewal of established contracts, labor stoppages are always a possibility yet rarely a surprise. Nonetheless, long negotiations have a crippling effect on schedules, contracts, supply chains, and ultimately profitability. To combat this, manufacturers must identify the financial impact of immediate and extended walkouts down to the plant level.
Scenario modeling provides the means to not only determine this effect, but to create and test plans aimed at maximizing minimal labor resources, managing raw material and finished goods inventory, and optimizing overhead costs – all while easily tracking a strike’s fluid impact on revenue.
Preceding a strike there’s often speculation as to what plants would be targeted and for how long. Now manufacturers can construct a prediction model and apply that to the effected plant(s) and projected timetable. This will help to determine the impact of a walkout down to a manufactured part number level.
This data can be used to:
- Evaluate impact on production line schedules to manage inventory and operating patterns
- Communicate to supply base
- Predict revenue impact
With such details in hand, management teams can communicate the impact of a walk-out by part number throughout the organization within minutes of a strike announcement. This can be especially helpful with parts that are common across vehicle lines. Without this level of detail, suppliers would not be able to confidently determine the impact attributed to a strike versus other market changes.
Global unrest
The war in Ukraine, conflict in the middle east, the world is seemingly on the brink. How will escalation or de-escalation impact business? And what about China’s relationship with Taiwan; will an invasion shut down the supply chain completely? The ramifications of such events on a company’s current direction and potential options must be painstakingly evaluated and accurately quantified.
Semiconductors, for example, are critical for industries across the board, what happens if Taiwan or China ceases production or disrupts South Korean exports? And consider European manufacturers who are seeing supply chain disruptions from the neighboring war. Because manufacturing enterprises are widely dispersed with extended supply chains, it’s becoming increasingly critical to thoroughly quantify the rippling effects of events half the world away.
How it works
In scenario modeling analysts change variables and observe the impact of these inputs on key metrics to explore potential outcomes. Ideally, multiple versions of these models are created to account for different or extreme scenarios, such as optimistic, pessimistic, and worst cases.
Identifying and quantifying key parameters that influence outcomes early in the process ensures a comprehensive and accurate representation of the system being modeled. Multiple attributes, such as economic, resources, technical factors, and so on must align with primary objectives and be interconnected to simulate realistic conditions.
By using a range of variables and scenarios, models account for potential variability, uncertainties, and dependencies. Robust data sources, consistency in measurement, and sensitivity analysis are essential to refine attributes and predict complex outcomes accurately. This enables decision-makers to better understand risks, trade-offs, and impacts.
Manual approach
Scenario modeling was traditionally a labor-intensive exercise that consisted of manually adjusting a limited set of assumptions and inputs in a spreadsheet or Excel. Because conclusions were often derived using historical data and judgment, results were generally subjective and often limited in terms of both scope and depth. And since calculations are handled manually or through basic formulas, analyzing complex interactions or large datasets becomes challenging and error prone.
Manually updating data or assumptions across multiple scenarios requires significant effort. This severely limits the ease and frequency with which scenarios can be adjusted making multiple iterations often impractical. Just as critical, manual processes lack the flexibility and speed of automated modeling tools making it difficult to respond quickly to changing conditions.
Automation
Manual modeling approaches rely on historical data sets which only go so far in predicting the future, especially with unforeseen and massively disruptive changes such as the 2020 pandemic. And how many manufacturers even had access to such data?
Aside from accelerating the process, a significant benefit of an automated solution, such as Campfire, is that the system becomes a repository for data.
“Without a centralized system, data is widely distributed with no reliable history associated with that data,” explained Meyer. “How can we make data-driven decisions to plan our business if the information is unavailable, unreliable, or incomplete? This undermines any ability to plan with any level of confidence.”
AI and scenario modelling
Nothing is complete these days without considering the influence of Artificial Intelligence. And to no one’s surprise, AI represents another leap forward in scenario modeling automation. Traditional approaches rely on limited datasets and human-defined rules, which can fall short in accurately capturing the nuances of dynamic systems. Conversely, AI, especially through machine learning and advanced analytics, can process vast amounts of structured and unstructured data to uncover intricate patterns and relationships, enabling more robust, adaptable models.
A significant advantage is AI’s ability to quickly handle what-if analyses across multiple variables, uncovering possible futures under varying conditions. Advanced algorithms can quickly generate scenarios based on historical, real-time, or even projected data offering insights to support critical decision-making in uncertain environments.
While some may classify AI as potentially disruptive to data-related activities, including forecasting, Meyer believes that its biggest contribution is this ability to continually learn and repeatedly model and refine scenarios. And Campfire development is on the forefront of extending AI to address business challenges.
“Perhaps the most significant contribution of AI is the ability to continuous learning, mine for information and refine models as new data becomes available,” he said. “This adaptability makes scenario models more accurate and actionable over time. By integrating and leveraging AI, organizations can enhance predictive capabilities, improve risk management, and make strategic choices with greater confidence in a rapidly changing world.”
A changing global landscape
While today’s consumers are fortunate to have a widening selection of product types, sizes and styles from which to choose – this adds yet another layer of complexity for manufacturers.
“In the automotive industry scenario modeling was relatively easy just a few years ago even though it had already become much more complex when Henry Ford offered the Model T in Any color as long as it was black,” concluded the automotive supplier’s executive. “Today consumers have literally hundreds of choices and, because BEVs don’t require an engine or transmission, they’re able to offer an ever-widening range of styling. This makes it increasingly difficult to predict what consumers are going to opt for. So, how can an OEM or supplier accurately predict what models will sell at a number at which they can breakeven?”
While navigating the unknown is essential for any business, today’s manufacturing enterprises are increasingly global and diverse, and uncertainties come at a faster pace with even greater consequences.
“With multiple product lines, vehicle programs, disperse plants, and partnerships, a supplier’s business is tremendously complex, and interdependent,” said Meyer. “Consequently, traditional methods to gain business insights and model what ifs are no longer sufficient to effectively quantify and respond to disruptions on an international scale. Business has simply become too complex. And scenario modeling allows manufacturers to keep their finger on the pulse of today’s dynamic and fluid business environment.
Companies are demonstrating foresight and leadership by successfully navigating today’s complex manufacturing landscape. This is exactly our ambition: To be mission critical in helping manufacturers to achieve results not previously possible to safeguard the business and the interests of stakeholders.”
The bottom line is this. There are countless unknown events lurking in the days, weeks, months, and years ahead. And whether these events result in crippling disaster or great opportunities depends on your level of preparation.
