In this age where we bask in torrents of overwhelming data, we must pause and ask, as we used to say in the military, what bits of this information comprise actionable intelligence? Most importantly is which bits can be data-mined for analysis which will contribute to continuous improvement in your operation?

BACKGROUND: In my experience in working with many firms, an often-overlooked opportunity exists to data mine product returns to suppliers, or from customers and/or RMA (Return Material Authorizations) activity, or reported discrepancies, for possible quality issues. Among firms that do track such data, there is great variation in the level of data mining occurring.

There is no question that for firms with robust tracking of this data, when quality issues are identified it may drive as applicable:

• Flagging, or requalification of suppliers.
• The need for additional training to prevent recurrences.
• The revision of existing procedures.
• The creation of new procedures.
• Triggering your Corrective or Preventive Action Process.
• Possible reporting of Suspected Unapproved Parts.
• Possible submission of malfunction and defect reports (if you’re an MRO or airline).

Regarding product returns from customers and/or its RMA activity, it’s interesting that none of the FAA AC 00-56, ISO/AS, ASA-100, or AFRA BMP standards appear to require the tracking of this data. ISO/AS/EN may infer or encourage such data to be tracked but it is not specifically called for and so once again there are some ISO/AS/EN firms that do, and some that don’t. So, if you choose not to analyze this data, you are not literally breaking any standards or regulations. For firms with Quality Systems not based on ISO/AS/EN, this is rarely tracked.

Regarding returns to suppliers or reported supplier discrepancies, standards like the ASA-100 require that a ‘Quality History’ for the approved suppliers be established.

CATEGORIES: The broad issues under consideration here naturally fall into three types of data with their own peculiarities and thus should be tracked separately:

• Product returns from customers.
• Product returns to suppliers.
• Discrepancies identified by customers, or by you regarding supplier parts, and both of which did not result in returns of the product.

DATA COLLECTION: If you’re convinced of the need to monitor this activity, the initial challenge arises from how you will gather the data.

• Product returns from Customers:
  • If your ERP system has built in features to facilitate RMAs for customer returns, this is a good source of data to tabulate, analyze and act upon. Make sure all your employees are using the RMA for such activity.
  • Don’t overlook warranty claims from your customer in this data mix.

• Discrepancies reported by your customers, but which did not result in product returns:
  • In this entire article this is perhaps the one issue that should be looked at critically. Effective and methodical collection and analysis of this data has the greatest potential to solidify a strong and mutually beneficial relationship with your customer.
  • “You don’t know what you don’t know”. The difficulty in obtaining every instance of a customer issue is directly proportional to the size of your company. The bigger you are, the greater the potential pool of employees interfacing with your customers, and if so, does each one have the discipline to uniformly document or report a customer issue in such a way that it can be collected and analyzed? So, just how are you collecting this information? If not, start now!

• Product returns to Suppliers:
  • Consider using the Claims section of your ERP system.
  • If you are using a Receiving Discrepancy Log or equivalent, also consider this to be a source of data. Make sure that even the minor issues are logged.

• If the data is dispersed in your system and not easily retrieved, consider finding someone that is handy with Crystal Reports to write a script that will automate the extraction and tabulation (how the data is presented) for either scenario (Returns from Customers, or Returns to Suppliers).

DATA MINING: Regarding the data which either of the three scenarios creates, the mining aspect would consist of the following:

• Accurately tracking the data- Make sure there no go-arounds or discreet off-the-record activity, see below.
• Analysis- Tracking and graphing the data is not enough. Here’s where the skills of your staff can shine. See Analysis section below.
• KPIs – Consider instituting Key Performance Indicator levels for the subsequent data.

ANALYSIS: An employee who is good at analysis is always a rock star on the staff. Analysis not only requires a command of the subject material, but skills at connecting the dots - taking apparently disparate points of data and seeing common connections. Effective skills often reflect a bit of creativity in this processing.

• Consider that there may be interplay between Returns from Customers and Returns to Suppliers. For example, your customer returns material to you on your RMA resulting on your returning it to the supplier.
• Minimally, consider using Pareto Analysis to drive your corrective actions.
• The many root cause analysis tools may be called upon.

BEWARE OF UNDOCUMENTED UNDERREPORTED ACTIVITY:

You have a favorite customer. They have been tracking the discrepancies caused by your shipments to them. Very few of these resulted in product returns to you via RMAs, and your sales staff have been rectifying each issue directly with the customer. Suddenly, you stop getting POs from them. It turns out that like so many major customers, there are set limits with quality issues which, once exceeded result in your being restricted from further business activity. When your company is apprised of the circumstances, your QA Manager is held to answer but was never made aware of the activity in the first place. Whose fault is this?

It's similarly interesting that some of the product return activity from customers may be deliberately underreported or handled in such a way that it does not draw too much attention within the firm. For example, the firm may be using an ERP system that has an RMA capability built in, but when asked how many RMAs have been issued to their customers for returns, they appear proud to say that there have been none or its remarkably low; probing further it’s discovered that certain salespersons have deliberately gone around the RMA system and discreetly handle the return with emails and personal intervention. The QA Manager remains in the dark.

Put the right data to work for you; be a rock star with your customers; make it happen…

Over ‘n out

Roy ‘Royboy’ Resto

www.aimsolutionsconsulting.com

The content of this article was written without the assistance of any AI programs.