Introduction

Within any company, data and documents associated with customers, orders and products flows through the organisation as it processes transacted business. In the case of manufacturing, the main process that manages transacted business is the order-to-cash process. Here, order data can enter the company via multiple channels, e.g. call centre, sales representatives, via the internet or via inbound electronic messages. In most cases this means that orders are captured in a number of different front office systems, all of which can then trigger execution of the order-to-cash process. Customer data, product data and order data associated with these transactions could therefore potentially reside in multiple systems. Once orders have been placed, they need to be collected and collated so that ordering of materials and accurate production scheduling can take place. From here the products are then manufactured, inspected, despatched, and delivered to customers whereupon invoicing can take place.

The challenge for most manufacturers is to execute this order-to-cash process error free, efficiently and at low cost while producing high-quality products and meeting customer delivery dates. In addition most manufacturers want to balancing supply with demand to optimise inventory. This depends on accurate planning, sales analysis and prediction of demand, all of which are analytical processes. Just imagine then, the impact on core manufacturing operational and analytical processes if the data flowing through these processes is unreliable.

What Is Data Reliability?

Data reliability is about guaranteeing that core manufacturing data is secure, correct and complete wherever it is used throughout the enterprise. It is also about the meaning of that data being clearly understood everywhere it is used. Even if data is correct, ambiguous naming may well render it unusable simply because business users do not understand what the data means. Reliable, trustworthy data is therefore dependent on two things being in place for every manufacturing data item in use wherever that data is used. These are:

• Data Quality – i.e. actual data values being correct and complete
• Metadata Quality – i.e. commonly understood data definitions

Only when data is trusted can it be used in confidence in all manufacturing operational and analytical process activities. Guaranteeing reliable data, therefore, is an obligation all companies should strive for. This means companies need to invest in the necessary people, processes and technology required to govern their data on an enterprise wide basis.

This paper examines the impact of unreliable data on manufacturing companies. It then defines the requirements needed to guarantee data reliability in manufacturing and offers a practical approach to creating and governing that data. It then shows how you can get started in making trusted data available in to help improve operational efficiency, planning, inventory optimisation, customer service, compliance and profitability.