How to ensure that analytical CRM solutions don't fall short in achieving effectiveness.
Posted Jan 18, 2005
CRM systems were designed to automate existing processes--reducing the time to complete manual tasks from days to hours or even minutes. However, this increased efficiency assumes that the original processes being automated are optimal. As a result, CRM systems can actually increase the rate at which organizations make mistakes. These organizations are efficient but not necessarily effective.
To address this shortcoming, many CRM vendors have added reporting and analytics to their products. These capabilities allow organizations to drill down into the data, trying to discover unknown trends or potential abnormalities. This emphasis on understanding operational data has driven growth in the business intelligence and analytical CRM markets.
While analytical CRM is a step in the right direction, most deployments have fallen short of expectations due to several challenges:
Management of unwieldy volumes of data
Modeling and integration of CRM and non-CRM sources
Explosion of metrics without any business context
Emphasis on transactional data that only reflects the past
Even with the plethora of data used in analytical CRM systems, it is rarely enough to give a complete picture of the business. Successful analytics requires substantial investment in integrating disparate data sources, organizing desired elements into consistent structures, and dealing with inconsistencies and omissions. Even when the modeling and integration issues are resolved, only a small percentage of the resulting "ahas!" are actionable as they lack business context.
The lack of context is compounded by the fact that most data in CRM systems represents information on the past. Analyzing historical data is akin to driving while looking in the rear-view mirror and limits an organization's ability to proactively drive in their chosen direction.
Rather than starting by analyzing operational data, organizations should instead start by communicating specific business goals. Are they more concerned about brand awareness or lead generation? Should they focus on reducing the cost of service or deepening their relationship with their most profitable customers? By articulating their strategic objectives in ways that every stakeholder can understand--not just strategic planning groups--team members become more motivated and can better manage their day-to-day activities, increasing the likelihood of achieving the organization's goals. If they also base their decisions on leading indicators and not just lagging metrics, organizations can monitor their incremental progress and make pro-active changes to resource allocations.
Organizations have started making a fundamental shift from worrying solely about efficiency to emphasizing effectiveness. This shift has given rise to increased interest in analytical CRM--the use of business intelligence technologies to analyze data in their operational systems. Unfortunately, most deployments have failed to live up to expectations because their results are not in the context of the company's goals. Customer-focused organizations should emphasize the widespread understanding of objectives before embarking on detailed analytics. The road to improved performance is out there but it doesn't start with data.
About the Author
Jonathan Becher is CEO and president, of Pilot Software
and is chartered with providing the overall strategic direction of the company. Leveraging his 15 years of operational expertise managing and growing technology companies, Becher leads the company's efforts to deliver relevant and innovative performance management solutions to the market. He is a frequent speaker at industry conferences, an active member of the performance management community, and author of multiple papers on a wide range of subjects. Prior to Pilot Software, Becher was interim CEO and president of Accrue Software; and president, CEO and cofounder of NeoVista Software. Earlier in his career, he held a variety of senior roles at MasPar Computer Corporation. Becher completed his MS in computer science from Duke University and a BS in computer engineering from the University of Virginia.
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