As decision support specialists, we generate the operational and financial information that companies require to optimize use of business resources. We do this by developing business models that companies use to achieve "best case" performance through cost efficient use of resources. Nothing is more costly to a firm over time than suboptimal performance caused by the wasteful use of resources. Cash balances become depleted; investment opportunities vanish; and competitive pressures force companies to lose market share. Our models eliminate these possibilities by defining the changes a business can make to marketing and operational activities so that maximum performance is achieved.
Your Decision Support Requirements
Typically, companies achieve success by making cost effective decisions on how resources should be allocated and used to produce and sell products and services. A company
might allocate resources to meet production and sales targets per product while minimizing total operating costs. For fixed levels of production and sales, such cost minimization also maximizes income.
Alternately, a company can evaluate resource allocation for multiple production and sales targets per product and then select the combination of targets that maximizes revenue, income or some combination of both these outcomes. Regardless of how your company defines the outcomes for success, Business Optimization Services will support your needs for generating the right information so that you can make the right decisions to capitalize on present and future business opportunities.
We develop our business models in EXCEL spreadsheets using SOLVER applications. Typically, a SOLVER business model is structured to include: a) data values, b) control variables and c) one or more outcome variables. The data variables can include such items as unit costs for different materials or wage rates for different types of labor used in a particular production process. Control variables are the decision variables selected by company management to maximize (minimize) values for outcome variables. Decision variables can include such items as the number of units produced or the frequency of email marketing campaigns for different products. Last, outcome variables capture the results that a particular company selects to optimize, typically maximize for income or minimize for cost. In operating the model, the user populates the model with the relevant data values and then activates SOLVER to generate the control and outcome variable values that define optimal performance. These values are available to the user in designated cells, defined according to the model structure.
Examples of SOLVER Applications
Consider the following
examples showing how we can support specific decision requirements through our
model building approach.
1. An umbrella manufacturer faces highly seasonal demand due to local climate conditions. To serve its seasonal demand pattern, the manufacturer can follow a production or inventory “smoothing” policy. There are cost trade-offs to consider in determining which policy to follow. With production smoothing, the firm minimizes production costs by relying on permanent workers to produce at average demand per month. Inventory builds during slack demand periods and then reduces during peak periods. With inventory smoothing, the firm varies production per month by hiring temporary workers and using overtime during peak demand periods. Inventory levels and related carrying costs are reduced but personnel-related costs increase from hiring workers and use of overtime hours. The company has forecasted sales per month for the next year and desires staffing levels for permanent and temporary workers and a mix of regular and overtime hours from each that minimizes total production and inventory carrying costs.
2. A firm delivers goods from its warehouse to retail centers using its own fleet of trucks. Trucks deliver goods on a periodic basis to each center to service each center’s demand for goods. Each truck has both capacity and time constraints. Capacity constraints are measured in maximum allowable total pounds per trip and time constraints are measured in maximum allowable total mileage per trip. The firm desires to evaluate its current route structure and change it as necessary so that the sum of total distance traveled for all trucks is minimized; subject to the capacity and time constraints for each truck and each trip starting and ending at the warehouse location.
3. A firm advertises nationally a line of home cleaning products to households through periodic catalog mailings managed by zipcode. Catalog recipients submit orders to the company by mail and then the firm fulfills these orders through package mailings. The firm monitors orders and sales per order by month for each zip-code and finds that peak orders achieved immediately after a catalog mailing decline by a constant percentage from month to month for each zip-code until the next mailing. This means that a company can increase its orders and revenues by increasing its catalog mailing frequency but cost of goods sold, fulfillment and catalog mailing costs also increase as a result. The company desires to determine the income (profit) maximizing catalog mailing frequency for each zip-code.
4. A retailer orders and sells a full line of sporting goods products to a local community by ordering from several vendors, each of which carries some or all of the products sold by the retailer. The retailer’s data indicates that vendors located closer to the retailer sell the same product at higher prices than those that are more distant. Also costs per order per vendor vary according to distance from the retailer’s location. This means that a cost trade-off exists between prices charged per product and ordering costs from particular vendors. The retailer has forecasted demand for each product carried for the upcoming year and needs to develop an order profile by vendor that meets demand while minimizing the total of product, ordering and inventorying carrying costs. The order profile needs to include the products to order from the vendor, annual amounts by product, the order quantity by product, and the ordering frequency by product.
We would be happy to discuss your business decision needs in more detail. Write us at email@example.com to receive your free demo packet of models indicating solutions to the four cases we describe. These are yours to keep without further obligation. After discussion and review of your business requirements, we will chart your path to better decision making by developing the models that you need for optimization of business outcomes.