Bringing Price Optimization to Manufacturing
While PLM platforms often dominate manufacturing-specific software news, analytics for digital manufactures is steadily gaining momentum. A recent example can be seen at General Electric, which hopes to leverage data from thousands of sensors throughout a factory to enhance quality control.
But you don't have to be a manufacturing giant to take advantage of big data, as Horizon Milling demonstrated through its successful implementation of MarginMax. A software-as-a-service offering from Zilliant, MarginMax is a price-optimization platform aimed at helping manufacturers to meet their goals for revenue and volume.
The goal of price optimization services is to adjust customer prices without putting revenue at risk. In MarginMax's case, the software works by analyzing the past 18-24 months of transaction data and looking at who the customer is, how often they order, and what products they order.
Zilliant CEO Greg Peters estimates that MarginMax looks at around 100 attributes related to customers and their orders, off of which they can glean which attributes influence buyers and their purchase decisions.
The next step is to organize that customer data into clusters through what is called “segmentation analysis.” This creates a number of discrete customer profiles associated with each price range. As the analysis heightens its level of detail, more potential pricing segments can be identified, and sales representatives can better determine how to appeal to their target customer. In general, having more segments is more favorable, as it is easier to pinpoint the purchasing trends of each buyer, helping sales representatives to better determine how to appeal to their target customer.
According to Peters, MarginMax typically boosts the number of identified segments from a few dozen to several thousand.
The goal of segmentation is to help a narrow product range expand its customer base by tailoring specific product packages to fit a broad range of potential prices. Thus, both low and high-budget customers feel satisfied with their purchase. This often works by removing some options and simplifying packaging to appeal to low-cost buyers while adding additional options to appeal to customers who can spend more money.
With this data, the responsiveness of price relative to the available quantity of a product can be calculated for each segment. The optimum production volume per each price can be pinpointed, helping Zilliant to tailor prices depending on a customer's business objectives in the marketplace. In certain segments they may want to drive volume, whereas in others they want to drive margin.
Peters believes this is especially important to manufacturers due to the growing complexity of the industry – manufacturers are producing more products and looking to appeal to more customers. Configurable products only add to the overwhelming amount of factors that a company must consider when determining their customer base and price point. By employing pricing analytics, companies are better able to eliminate the guesswork on both the sales end (price optimization) and the manufacturing end (capacity optimization).
One such manufacturer that Zilliant has helped is the aforementioned Horizon Milling, a joint venture between Cargill and CHS that specializes in flour milling.
Already, manufacturers such as Horizon have numerous PhDs on staff who work exclusively to develop the characteristics and define the ingredients of the products that Horizon takes to market. Like many other companies, Horizon has invested a significant amount of money in developing the best possible product for their market, but little money into determining the optimum price to make that product successful.
Pinpointing and helping customers realize the actual market value of their products is where MarginMax is designed to come in.
Although MarginMax's first application for manufacturers to determine how much of a product to produce, the software has also demonstrated its usefulness in optimizing factory utilization.
Zilliant describes the mill utilization benefits of MarginMax as giving a more detailed and actionable picture of what the future will look like given specific pricing conditions. From there, companies can adjust production volumes and factory operation hours accordingly to meet margin goals.
For example, a company might consider running their factory on a weekend to increase capacity. “While you don't have an increase in fixed costs, your variable costs are going up because of the weekend labor force,” noted Peters.
To address this question, MarginMax looks at weekend labor costs and increased production volume to calculate a new price and resulting margins. Ultimately, this can help manufacturers to decide not only how much of a product they are going to produce, but also help them fine-tune the goings-on of their plant.