Understanding the “M’s” – Master Data, Metadata and Metrics.
Master Data – This is the structure of how we look at our data – Customer, Products (services), Vendors and our organization as the main elements. It includes attributes like names, locations, colors or sizes and may include a hierarchy that shows us a customer and its subsidiaries or one of our product lines.
Metadata – This shows how we define our data and how to find our information, how we use it, who owns it and why it is important. An example is who are our top ten customers by profitability? First, define customer. Does it include all customers rolled up to the parent or even affiliated groups? Next, define profitability. Is it defined as initial profitability, long-term profitability that includes returns and rebates or does it include cost of selling, customer support or other costs? Finally define the time horizon. Is it quarterly, annually, over multiple years and does the trend matter and why? Metadata gives us the contest to know how to use our data.
Metrics – This shows how we analyze our operations and drive the business. Includes high level Key Performance Indicators (KPI) all the way down to monthly, weekly, daily, hourly or even real time operational metrics. Each industry has its own KPI’s but some common ones are Profit, Costs, Sales, Customer Lifetime Value, Customer Satisfaction, Product Quality, Employee Satisfaction and Employee Turnover Rate. Some operational metrics are products manufactured, current inventory, products shipped, service hours logged, product or service backlog, number of defects, tickets closed, customer wait times or employee absentee rate. Clearly there are thousands of different operational metrics and many organizations tweak standard industry KPI’s to meet their needs but understanding the concepts is critical.