Customer relationship management (CRM) is no stranger to user adoption issues. Similarly, sales force automation (SFA) has been challenged with the adoption of new processes and technologies for more than a decade. Customer intelligence (CI) projects face the same steep climb to user acceptance as other CRM-related projects but with some unique challenges that other CRM projects may not encounter. Key barriers to user adoption include:
- Most users are not "required" to use reporting systems.
- Non-analytical executives are not information savvy and, therefore, do not expect their employees to be either.
- CI spans functions and systems, creating political hot spots.
- Self-service reporting can be perceived as an intrusion on already time-constrained employees.
To successfully overcome these barriers, CI teams use a combination of organizational change and process improvement techniques.
Embedding Analytics in Processes
Adoption of analytical systems can be accelerated by integrating reports, analytics and information access into the existing business processes. If a business process cannot be finished successfully or if the end result will be of less quality without leveraging the CI systems, users will be more inclined to leverage the new capabilities.
For instance, sales forces are beginning to leverage analytics to understand best practice sales techniques. CI systems integrate sales activity, calendar, task, opportunity and order information to understand the sales approaches that win specific kinds of deals. For instance, one software company knows that if they create an ROI estimate within their proposal instead of waiting for a follow-up presentation, they have an 80 percent chance of making the short list and a 50 percent chance of winning.
Knowing the power of this information, the organization added a step to their sales processes. After each deal is won or lost, sales management reruns the best practice analysis in order to see if any new best practices have surfaced, were further confirmed or have started to deteriorate. Sales managers then update the task templates that are assigned to various opportunities to incorporate new best practices. The analysis has a side effect of also increasing the use of the sales force automation system itself. The sales force is more diligent about logging their activities and tasks because they know that the information will most likely be valuable to them in the long run.
Performance management refers to the programs that govern our career path. These programs specify the following items:
- Qualities and skill sets required at different levels of the organization.
- Criteria that differentiate exemplary performance from the status quo.
- A process of how employees are evaluated and how that feedback will be distributed.
Some organizations religiously believe in the power of information and that fact-based decisions will generate profits. These organizations are integrating analytics into their performance management programs. Many organizations that are rolling out business intelligence systems are adding criteria to employee evaluations regarding leveraging information in their day-to-day responsibilities. Those employees who do not know how to access or leverage corporate information to evaluate the performance of their projects, including marketing campaigns, sales strategies, product offerings or investment decisions, are considered as not meeting expectations.
One organization's marketing department requires employees to understand the basics of predictive modeling if they wish to be program managers. This same organization also requires an ROI figure to be developed before each marketing campaign. It is impossible to create the ROI documentation without leveraging their reporting data mart to understand past performance of similar campaigns, product performance, revenue estimates and cost information. Not only is this a good example of embedding analytics into the marketing process, but program managers are evaluated on the accuracy and quality of the ROI estimates.
Leadership by Example
Leaders that believe in the power of information greatly influence those around them. Leaders who demand that employees not "guess" start to build a culture of leveraging information and tend to be successful. For example, a vice president of operations at one large Global 2000 company does not allow the following phrases to be uttered in his meetings: "I think," "Maybe" and "I am not sure."
Whenever he hears these words from his group, he excuses the one who expressed the phrase from the meeting and asks that person to use the data warehouse to get the answers. These rules do not necessarily mean that the group came to the meeting unprepared, because an ad hoc topic may have arisen. What it means is that the executive does not want to waste time on conjecture when the answer is only a query away. These rules have produced a group of lieutenants who take it upon themselves to generate information before important meetings and volunteer to retrieve the facts before the vice president needs to suggest the action.
Another example of leadership driving CI adoption is the executive who has better information than his employees. No one wants to be less informed than his or her boss. Everyone wants to be the one to shed light on a topic. Leaders who come to meetings with information that is readily available from the system set the tone for employees to keep themselves informed of the facts.
Build Your Champions
In every data warehouse implementation there are a handful of champions that "get it." They understand the value of information, they are hungry for it, they are innovative, they will expend great amounts of effort to learn the reporting application and the data. They are also the ones who do not care about canned management reports; they are the power users, the ad hoc analysts. These are the people who drive the ROI on a data warehouse investment.
The following process can be followed to cultivate and grow champions:
- Identify the people in the organization who need advanced information access to do their jobs effectively.
- Ensure that these people are involved in scope, requirements and design decisions to generate ownership.
- Provide these users with special one-on-one training for the data and application. Remember that training should be 80 percent focused on understanding the data and only 20 percent on the application.
- Provide superior production support for these individuals.
The product support point is possibly the most important point for those employees who are regarded as champions. If the team is slow in getting answers to champions' questions, if requested information and/or reports are not promptly produced or if data quality issues are not resolved in a reasonable amount of time, the champions will become disenchanted with the system. If champions feel the system is inflexible, does not meet requirements or cannot answer the "simplest questions," you will lose their support and possibly never gain traction on the system.
Training is an important part of the adoption process, albeit an obvious one. The less obvious part of CI adoption is an understanding of core business processes and the different individuals in your organization that will champion your effort. Focus items for your adoption effort should include:
- Identifying the specific business process that either requires business intelligence support or enhancement.
- Integrating business intelligence capabilities into performance evaluation programs.
- Supporting leaders who wish to drive an analytical culture.
- Providing exceptional communications and support to analyst champions who want to leverage the data warehouse.
The data warehouse is heavily influenced by word of mouth. If individuals start appearing at meetings with warehouse reports or executives start crediting the warehouse by providing timely information quickly, word will spread that people who are not utilizing the system are at an extreme disadvantage.
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