Businesses must constantly deal with uncertainty. We rarely know for sure what next quarter’s sales will be, whether our supplier deliveries will be on time, or what our inventory levels will be – let alone what competitor prices, future interest rates or exchange rates, or energy or commodity prices will be.

Experienced managers seek to anticipate change, not react to change. We make our best predictions of these factors, and perhaps plan for “best case, worst case and expected case” scenarios. But doing this can be very challenging when there are many products in sales, many suppliers and deliveries, and many possible ways to use resources – the materials, workers and money we have. With Analytic Solver, you can adopt a systematic, quantitative approach to these decisions, instead of a “seat of the pants” approach.

You can’t solve all problems at once, and building an analytic model does take some time, so your first decision often is to choose the business situation with the greatest potential payoff. Compared to other commercial software, Analytic Solver in Excel can drastically shorten the time it does take to build and solve a model.

Be More Proactive by Predicting Future Outcomes

If your company or department has been using “seat of the pants” forecasts of sales, delivery times or inventory levels, a systematic, quantitative forecasting approach can be worth the effort. Better data can help: For example, if you can obtain real-time data from your suppliers on their upcoming deliveries, that will certainly improve operations. But people who focus on “data” often miss the essential role of quantitative models.

Forecasting

If your problem is forecasting next quarter’s sales, and you’re not already using forecasting software, Analytic Solver can help. It includes full support for time series forecasting with ARIMA (auto-regressive integrated moving averages) and exponential smoothing, the best-supported and most-widely-used forecasting methods. If you have historical data, it takes just a few mouse clicks and dialog choices to build a forecast that takes both trends and seasonality into account. With better forecasts, you can be more proactive.

Machine Learning

If what you need is not forecasts of aggregate demand over time, but instead predictions of sales or customer behavior in individual cases (will this prospect buy, will this customer renew, will this machine fail this week), again Analytic Solver can help – this time with machine learning models, which make such individual-case predictions. It includes full support for a range of leading ML methods, from CART (Classification and Regression Trees) to Neural Networks to Ensemble Methods, again accessible with a few mouse clicks and dialog choices. It can even automatically choose the best method for you. Good ML models help your business be more proactive on each transaction or interaction.

Be More Proactive by Explicitly Modeling Risk

Better predictions can help you improve on the “status quo”. But predictions by themselves are just estimates of most likely outcomes – the actual outcomes can and will vary. Better predictions don’t make the uncertainty go away – especially for external factors like interest rates, exchange rates, or energy or commodity prices. But you can explicitly model the uncertainty. Many managers and analysts do this in a basic way with “best case, worst case and expected case” scenarios. But you can do much better with quantitative risk modeling.

Again Analytic Solver in Excel makes this far easier than other commercial software. There’s a good chance you already have a budgeting, forecasting, or other “what-if” model in Excel that lets you manually explore possible scenarios. With Monte Carlo simulation, you can quickly extend this to explore thousands of scenarios automatically. It includes powerful tools to model each uncertain variable (with probability distributions) and the interactions among these variables (with correlations and copulas).

You can examine individual “what-if” outcomes, display a wide range of charts and graphs of those outcomes, and automatically calculate dozens of statistics – from average, max and min to “value at risk” and “six sigma” measures – with simple Excel functions. This quantitative approach easily beats simple “best case, worst case and expected case” scenarios, and gives you greater confidence that you’ve covered all the possibilities.

Be More Proactive with Better Decisions on Resource Use

As we wrote earlier, even with better forecasts or predictions and quantitative risk modeling, making the best decisions based on this information can be very challenging when there are many products in sales, many suppliers and deliveries, and many possible ways to use resources – the materials, workers and funds we have. This is where an optimization model that uses those forecasts, predictions, and even quantitative risk measures can make all the difference.

Optimization directly addresses the need to use resources in the most efficient way possible. Each decision, to use material, workers, money or other resources for a specific purpose, is modeled in Excel. Constraints you add to the model account for limits on available materials or workers, space for inventory, money, etc. The optimization solver finds the best possible set of decisions, to maximize sales or profit or minimize cost.

An important caution: Most commercial optimization software doesn’t deal with uncertainty. Conventional models effectively treat input data (including predictions) as “fixed i.e. known with certainty”. But Analytic Solver can not only model the uncertainty, with the Monte Carlo simulation tools described above – it can find optimal solutions that explicitly take the uncertainty into account, with methods such as stochastic linear programming, robust optimization, and simulation optimization.

Consider these real-world applications:

Optimized Portfolio Management – Financial institutions can use predictions, simulations, and optimization to construct investment portfolios that balance risk and return. Whether applying the Markowitz model for portfolio optimization or using Monte Carlo simulation to stress-test investment scenarios, firms can make better allocation decisions.

Optimized Inventory Management – Anticipate demand, optimize stock levels, and minimize costs. With an optimization model that integrates demand forecasts, businesses can proactively adjust inventory replenishment strategies—ensuring stock availability without overordering or tying up unnecessary capital. Analytic Solver helps you balance supply and demand efficiently, reducing holding costs while improving service levels.

Workforce Planning & Scheduling – Companies can forecast labor needs and optimize shift schedules to balance cost, efficiency, and employee preferences. Crew scheduling models, for example, help airlines minimize labor costs while ensuring regulatory compliance and employee satisfaction.

Cash Flow & Capital Planning – Businesses can anticipate inflows/outflows, and optimize cash use, interest earnings, and capital investments. Working capital management models help allocate funds efficiently, while bond portfolio duration matching ensures financial obligations are met with the right mix of assets. Capital budgeting that integrates good forecasts and constraints on use of funds yields more rational, and ultimately better long-term decisions.

Transportation & Logistics Optimization – In fleet management and delivery planning, where fixed costs are high and demand often fluctuates, good forecasts as inputs to a multi-level, multi-commodity transportation model (a common type of optimization model) can ensure effective use of these valuable resources, and save lots of money compared to “seat of the pants” decision approaches.

The Competitive Advantage of Proactive Risk Management

Companies that become “good at” building and using forecasts and predictions, explicitly modeling risk and uncertainty, and applying optimization to resource decisions aren’t just coping with uncertainty – compared to competitors, they’re often turning uncertainty into opportunity. By staying ahead of disruptions, optimizing decision-making, and improving resilience, businesses gain a crucial competitive edge in an unpredictable world.

Are you ready to take control of uncertainty? Reach out to your account manager today for guidance to start leveraging the full range of powerful methods in Analytic Solver.