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Veteran reliability professionals have heard about various “reliability-centered” activities. Most are familiar with Reliability-Centered Maintenance (RCM), and many have extended the reliability-centered concept to equipment, process, and/or plant design (RCD) and operation (RCO). Does reliability have a place in the world of sales? I submit that it’s a critical function to involve in the reliability process, arguably the most critical.
Let’s start by deconstructing a typical sales and delivery transaction. In most instances, the sales organization consults with the customer to determine its needs in terms of product type, quantity, required quality and delivery expectations. After negotiation, the salespeople typically reach an agreement on pricing and terms with the customer and a contract is executed. Upon receipt of the purchase order, production schedules the job, manufactures the product in compliance with the company’s safety and environmental management policies and prepares the order for shipping to the customer. The customer demands product, price, quality and transport from the sales department. The sales department, in turn, demands that the production department manufacture the product to comply with the terms set forth by the customer, and the production department demands reliability from the machine, process and plant design team, and from the maintenance department.
On the surface, it appears that the issue of reliability is between the production department and the maintenance department on a day-to-day basis and between production, maintenance and the design team in the longer term, but that conclusion is flawed. Divorcing sales from the reliability equation creates a serious and potentially costly gap.
Often, the contract forged between the sales department and the customer contains negative covenants that are triggered by the company’s failure to comply with quality and/or delivery specifications. For example, failure to deliver on-time might trigger financial penalties that erode or eliminate the profit on the sale. If the delivered quality is off-specification, the contract typically contains a provision by which the customer can reject the shipment, forcing the company to ship the product back to the plant or another location, sell the product to another customer at a lower price, re-run the product through the process, etc. – all of which add cost.
When product is rejected due to non-conforming quality, penalties invoked for non-delivery may also apply, compounding the loss of profit. Even when no financial penalties apply, the company’s reputation and relationship with the customer may be adversely affected when there’s failure to deliver per the agreement.
Over time, despite the popular notion that most machines have a constant failure rate over time, the actual risk of failure for an entire plant or production line system decreases over some period following an outage or shutdown (infant mortality failures), then it typically levels out and begins to gradually increase as a function of time or production units (see figure). This occurs because some failure modes within the aggregated system are time-dependent and because of the cumulative effect of misoperation and/or the deferring of maintenance. Over time, the risk profile for selling, producing and delivering product changes. If modeled correctly, this data can be utilized to achieve the following:
1) Risk-rationalize the profitability of a transaction: If the sales department has negotiated a sale with a tough customer that forces the organization to accept razor-thin margins and assume the risk of negative covenants (e.g. non-delivery clause), looking at the projected profit on a straight, non-risk adjusted basis is simply flawed. It is analogous to evaluating an investment opportunity without considering the time value of money. When one incorporates the reliability risk factor into the transaction analysis, the sale may prove to be below the company’s required profit margin.
2) Rationalized investments in reliability: Candidly, the benefits of reliability investments can seem a little nebulous for some people. However, if the risk profile of the plant is defined, the value of reliability investments can be defined in terms of contribution margin per item for any given point in time. WOW! That puts things into hard dollars for which no stretch is required. It makes it easy to determine if the organization should spend more or less on reliability growth/improvement investments.
While relating reliability data and information to create risk-based production profitability estimates and incorporating that data into the sales process may seem new to the manufacturing and process plant reliability management community, you are probably accustomed to this process at a personal level. In essence, when you profile the reliability of a production line or plant as a function of time or other applicable factors, you create what amounts to actuarial tables to demonstrate the risk profile, much the same as a life or health insurance firm. These organizations understand that the human body follows the “bathtub curve,” which defines risk as a function of time. Adjusting for age and to reflect genetic predisposition and lifestyle choices, which are analogous to equipment/plant design, operations and maintenance, the insurance company sets the price of your premiums based upon a probabilistic risk profile. They clearly understand the relationship between risk and the profitability of each sales transaction. Shouldn’t we in the plant reliability management business do the same?
The methods for creating risk-adjusted profitability analysis are well-defined thanks to other industries, especially insurance. We simply need to apply these techniques in the plant. So in addition to getting plant operations, design engineering, and plant and senior management educated about reliability, I suggest you get your sales and marketing departments up to speed about the value of effective plant reliability management. Get support from sales and marketing, the voice of the customer, and the generators of revenue and margins supporting reliability within your organization and it will become much easier to get appropriate, cost-justified reliability improvement projects approved because it clarifies the relationship between reliability and the bottom line.
Drew Troyer, CRE and CMRP, is the co-founder and senior vice president of global services operations for Noria Corporation. Since leaving Oklahoma State University, where he served as an instructor, his professional career has been devoted to improving machinery reliability. He served as product manager for Entek/Rockwell Automation and as the director of technical applications for Diagnetics Inc. His lengthy client list at Noria includes International Paper, Cargill, Goodyear, Texas Utilities, Reliant Energy, and Southern Companies.