Improve quality performance, boost customer satisfaction and protect brand equity

SAS Field Quality Analytics

Detect emerging issues sooner. Find root causes faster. And shave months off your issue detection to correction time.

Provide early warning with patented analytic models.

Define, prioritize and correct issues faster than ever. Patented analytical models enable you to effectively isolate failure modes and identify their true root causes so you can make well-informed corrective action decisions. Advanced forecasting and reliability techniques (including Weibull) help you understand how issues will affect costs and customers so you can prioritize them and focus resources where they will have the greatest impact.
Reduce your detection to correction time.

Consolidate all relevant field quality data – including call center and work order notes – into a single, integrated view. Then apply predictive analytics to automatically detect emerging issues much faster than traditional analysis can – before they have a significant impact on performance. You could shave months off your issue detection time, leading to substantial savings in repair costs and greater customer loyalty.
Lower your warranty costs.

Earlier issue detection and shorter correction cycles could reduce your resolution time by up to 70%. You could also lower warranty costs by up to 20% by shipping fewer faulty products and decreasing the size and number of recalls. By shortening the time issues exist in the field – and reducing the number of customers affected – your risk of negative publicity through traditional and social media channels is greatly diminished. And that means fewer costly campaigns needed to help counteract damage done to customer satisfaction levels and your brand's reputation.
Easily implement enterprisewide operational improvements.

SAS Field Quality Analytics integrates seamlessly with the full SAS Quality Analytic Suite, including SAS Production Quality Analytics and SAS Asset Performance Analytics. A common code base and data model make it easier to implement enterprisewide operational improvements by enabling you to take a modular approach to adding analytic capabilities as your organization matures.

IDC research shows that 59.8% of manufacturers stated that warranty/recall management was business critical and that the business would stop without it. Unfortunately, organizations too often regard the warranty process as part of an aftermarket activity which has limited impact or no impact on the rest of the organization." Aly Pinder, Jr. Program Director, Service Innovation & Connected Products IDC

Get to know SAS Field Quality Analytics

Key Features

Get a comprehensive view of field quality by merging field performance data with key customer, product, manufacturing and geographic information. Then apply predictive analytics to identify issues quickly so you can address them proactively before they escalate and irreparably damage your brand reputation – and your bottom line.

Data management

Lets you consolidate data from disparate sources using a standard, extensible data model. Flexible database support lets you store models in SAS or third-party databases, such as SAP HANA and Hadoop.

Pre-built calculations

Addresses the complexities of warranty data with integrated business rules and algorithms for sales lag profiles, usage distributions, maturity calculations, seasonality adjustments, etc.

Interactive issue analysis interface

Accelerates the issue investigation process by enabling easy drill-down on one or more data points to get details on emerging issues.

Automatic anomaly detection

Monitors emerging issues by automatically detecting anomalies based on violations of analytically driven critical values or manually input thresholds.

Integrated text analytics

Extracts and categorizes essential information from large volumes of unstructured data and combines it with structured data to reveal patterns and uncover related claims.

Self-service reporting

Lets you easily create reports using simple selection filters to define data sets and other criteria.

Cloud native

Compatible with cloud technologies – including Docker and Kubernetes – for large-scale, elastic, multitenant, distributed services. Ready-made to take advantage of the large volumes of data generated by the IIoT.

APIs

Call data selections and launchers to retrieve the latest data, and transform it for analysis. Call calculations to deal with unique warranty-related issues, such as sales lag, usage, maturity and extrapolation. Call analyses to refresh output and populate reports.

View detailed features list

Organizations of all sizes are working smarter with SAS

A luxury appliance manufacturer

Automating manual processes, reducing errors and freeing up resources while cutting service incident rates in half.

The company used SAS to automate text-based coding of claims, which substantially reduced manual effort, increased accuracy and focused resources on problem solving. Feeding results into the automated early-warning process shortened issue resolution time and reduced service incident rates.
A global heavy equipment manufacturer

Using a single application to access a net view of all your business lines and seamlessly expand to include telematics.

SAS helped the company create a unified view of data across multiple brands, divisions and functions, as well as provide an early warning of potential incidents to enable a rapid response.
A regional automobile manufacturer

Cutting warranty costs by up to one-third.

SAS enabled the company to reduce issue identification and definition time by 70%, saving more than four months and netting the manufacturer over $2 million in savings in the first six months.