In Data Management, Data Quality

Every business cycle seems to see increased pressure on all types of organizations and companies. Customer needs change rapidly. Rapid technological advances make it difficult for cash-strapped companies to keep up. And the increasingly globalized economy introduces more and more competition from foreign companies with low overheads, lower staff costs, and less regulation.

The ability to make fast decisions and initiate flexible responses to sudden market shifts increasingly depends on the ability to collect, organize, analyze and deploy data at real or near real-time speeds. Faster decision making depends on four key organizational capabilities:

  1. A decision-making culture that values quick, clean and organized supporting data. You cannot improve what you cannot see. Lean, flexible, and fast business must measure key operational performance measures and be able to do it in near real-time so that accurate business information is at hand for making adjustments more quickly.
  2. Established processes for cleansing, maintaining and enriching data. Top companies invest time, energy and cash, not only in their information technology, but also in developing data collection protocols that insure the ongoing quality of data collected.
  3. Real-time measurement of operational metrics. New technologies in both hardware and software make it possible to collect, to process and to distribute data quickly. Speed alone isn’t everything, however. You have to insure that you’re collecting the data that the various systems within your business need (manufacturing, inventory, marketing, sales, etc.).
  4. The ability to assess the data needs of all business systems/functions across the organization. Some industries and organizations, by their nature, collect massive volumes of data in their daily operations.  Capturing data is only part of the challenge. Turning raw data into meaningful analysis quickly and disseminating it to key decision-makers within the company requires every bit as much thought and planning if company leaders are going to have the business information they need to compete effectively.

To reduce the critical query to response time, top performing companies have had to deploy advanced technology in three categories:

  1. Data Collection – Technologies that are effective at finding, capturing, organizing, cleaning, appending and enriching data help insure that data is more efficiently used by the company’s analytical systems.
  2. Information Assembly – Advanced analytical tools ask questions based on the data collected, apply business rules and, modeling techniques, then analyze and assemble the data into useful business insight.
  3. Insight Delivery – Carefully developed data gathering and dissemination protocols deliver the resulting business insights to key decision makers within the organization in a timely manner; often within a matter of hours. In critical situations, data systems may have to deliver information almost instantaneously. Today’s just-in-time manufacturing systems, for example, depend on real-time production data to insure materials are delivered to assembly lines as they are needed.  This reduces the necessity for massive inventories of parts and materials and reduces production costs so that domestic manufacturers can compete with overseas companies.

Technologies deployed in these categories create an environment that supports faster decision-making. Tactical or operational dashboards improve daily, hourly or real-time visualization of the metrics that support the decision-making process.

SAP’s Michael Brennan recommends that companies that wish to streamline their decision-making process take the following steps:

  • Start to measure “time to information” – However insightful a piece of business information is, it’s useless if it’s not delivered in time. Take a hard look at how long it takes to go from raw data to useful information.
  • Develop in-house programs to develop, coach and train analytical talent – You can bring in hired guns with the requisite experience, but in order to develop long-term capacity growing your own is a proven strategy for creating an efficient, loyal data collection and analysis team.
  • Investigate technologies to improve data quality – Data timeliness, relevance, ease of access, accuracy, and immediacy are essential to good business decision-making. Pay attention to keeping data collection, information assembly, and insight delivery up-to-date.
  • Develop predictive modeling applications that incorporate real-time data – Accurate predictive models help you to leverage real-time visibility and quality data to improve operational decision making and to sharpen your ability to react quickly to both threats and opportunities.

To avoid being buried in the astronomical amount of data pouring into your databases, it’s essential that you have systems in place with which to manage the flow of that data and turn it into good business decisions. Don’t be content waiting for days or weeks for critical information when it’s already in your databases waiting for you to tap it. Instead of reacting to competitive pressures or emerging markets once the momentum has already shifted, get ahead of your competition and be there waiting when customers come looking for the goods and services they need.