Four Steps to Averting Data Scatter
Companies can use the following four steps, discussed in detail, as a tool to dig out from underneath their piles of data.
1. Eliminate Organization Barriers
For many companies, performance measurement issues go far deeper than simply trying to more effectively leverage IT systems. In many cases organizational dynamics are the core barrier to successful performance measurement program. If this is the case, the company needs to focus on understanding and overcoming the people issues, political issues and policy issues that prevent defining a single truth on performance management to which people will agree and trust. Corporate cultural issues are often the greatest barriers to achieving partnerships internally and externally.
One example of organizational barriers to performance management is that of local suboptimization in which employees suboptimize for departmental objectives, often to the detriment of the larger organization. For instance, a procurement manager goes with a low-cost supplier to meet department cost reduction goals without first understanding if there are quality tradeoffs that will perhaps decrease the throughput at manufacturing. A company that experiences such cultural and organizational hurdles needs to make drastic changes in corporate culture to foster teamwork. Internally, no matter how performance measures are collected, no single measure can exist that will measure cross-functional objectives. A policy is needed from the top that requires departmental collaboration. A cross-functional leadership team then needs to be charged with developing measures that relate to broader interests.
Once a company has overcome its organizational barriers, it can then begin to look toward technology to enhance its performance management program.
2. Corral Your Systems
Once a company has clearly determined goals and objectives and has selected the right metrics to support the business, it needs to assess the current systems architecture in light of the performance measurement program. This begins with analyzing the source of the information required and the complexity of integrating the data to support the need to roll up and drill down in one performance management system. Given the requirement to universally define and share metrics, IT should plan for an integrated data repository of detailed transactions and complex data calculations.
A primary reason for data scatter is that most companies do not have performance metrics from integrated software running their business. Instead, companies rely on performance metrics drawn from many different systems, like enterprise resource planning (ERP), customer relationship management (CRM), warehouse management systems (WMS) and transportation management systems (TMS) to name a few.
To make matters worse, many companies augment these execution systems with offline metrics tools such as spreadsheets, databases and flat data files. While each system and offline tool provides important information about a company's performance, the downside is that the data is defined, collected and stored in different ways.
IT leaders need technology architecture with a data collection process that can tap into the disparate systems to extract and organize detailed performance measurement data. Depending on the systems environment, a data warehouse that is either custom built or bought may help corral disparate systems. It must be able to address the organization's need for actionable information. The performance measurement team should include a community of business leaders and users to drive a solution design that supports balanced measures from detailed transactions, promoting agreement and trust. With strategic management in mind, business leaders need to drive each other toward business process measures.