Author's Note: This is the fourth column in a series of five that describes the different maturity levels pertaining to a customer intelligence road map.
Data integration is absolutely critical for gaining the types of insight needed to support a customer-centric organization. Organizations that have successfully completed data integration initiatives have obtained increased insight into their customers, partners and business operations through standard reporting techniques or business performance management (BPM) applications.
However, while these initiatives provide access to information, there is little support for helping companies make decisions or evaluating those decisions once they have been made.
For example, a sales management team may be able to see a slowing pipeline, but the information doesn't show solutions for a sluggish pipeline, whether the problem has occurred before, actions taken when this problem occurred in the past or whether past attempts to solve the problem were successful.
Decision enablement (DE) systems move organizations closer to real-time (or right-time) decision making by providing the tools to document, track and research past actions. DE applications integrate with the core customer intelligence infrastructure and have the potential to integrate with BPM tools by connecting raw data, information and analytics to a system or process that can execute on a decision. DE systems help information-based, fact-oriented organizations leverage that information for competitive advantage.
Identify Issues and Proactively Notify Stakeholders
DE systems use alerts, notifications or proactive messaging to help companies identify problems and notify stakeholders of the problems.
Alert technology comes in a variety of shapes and forms, including standard reporting tools, networking or messaging software and enterprise. Regardless of the technology used, these alerts must manifest themselves across multiple mediums, including reports, e-mail, voice mail, the Web, PDAs, etc.
Typical alerts set up in a customer intelligence infrastructure may include: sales pipeline and forecast thresholds, customer profitability increases and decreases, customer service load balancing issues, marketing campaign performance issues, customer issue resolution problems either at an aggregate level or for specific high-value customers and sales close date discrepancies. For example, a sales manager using an alert when tracking the company's current sales forecast would see the following information:
- The problem: The sales forecast is 20 percent below projections.
- The meaning of the threshold: We have identified that there is always a 10 percent range in the sales forecast, so the 20 percent threshold tells us that we have a significant discrepancy.
- The possible ramifications: Missing the sales forecast has an adverse impact on profitability, bonuses and possible guidance in the marketplace.
Figure 1: Decision Enablement Process
Recommendation of Specific Actions
There are typically two approaches companies use to recommend specific courses of action once a problem is identified and the stakeholder has been notified. The levels of sophistication between the two approaches are usually separated by the amount of actual "suggestion" that the system is revealing versus the amount of "homework" that the user must do. Companies should decide which approach best suits their organization. Examples of "homework" approaches may include:
- Leveraging the company employee directory to find subject-matter experts who may be able to help with the issue.
- Utilizing the corporate intranet to enter searches for documents, presentations and/or e-mails that may have the answer the user is looking for. This solution typically requires a document management system that has stored, indexed and categorized various documents to be retrieved via search.
"Suggestion" approaches are typically used by companies already familiar with DE systems who can then link to specific solutions at the time of the alert. An example of a "suggestion" approach is integrating a document and database library that can link thresholds to solutions and the documentation regarding the solutions, allowing organizations to automatically recommend actions. This implies that at each decision point, the course of action is documented in a structured way. Very sophisticated organizations may even have metrics on the performance of different actions.
Using our sales forecast example, we can see a course of action being chosen by performing one of the following actions:
- Connecting experts: The sales manager searches the corporate intranet for the employee who formerly held his position.
- Document repository: The sales manager searches the corporate intranet using the key words "sales forecast problem," which retrieves a presentation to the vice president of sales, CFO and CEO from two years ago describing possible options for a sales pipeline issue.
- Threshold search: Using the company's customer intelligence portal, the sales manager runs a report that filters on threshold "sales forecast." The report shows different solutions, the last time the solutions were used and provides a link to the documents describing the solutions.
Similar to recommendations, there are several different levels of sophistication to consider when implementing processes for taking action. These levels range from extreme automation to a formal, manual approval process before proceeding with courses of action. The level of sophistication may be influenced by organizational structure and culture as much as technology. Examples of action process may include:
- Managers may need to seek approval before making specific decisions. Workflow software can automate the proposal/approval process or informal communication may be used.
- Decision-makers may need to log into the actual operational application to make changes. For example, sales managers may modify the sales process in the sales force automation application requiring regional managers to accompany sales representatives for all presentations to increase close rates.
- Some sophisticated organizations may be able to display courses of action right in their alert. In this case, there may be integration between the alert and the operational system to automatically make an adjustment. For example, the sales manager may hit the button on the alert marked "Require Regional Manager for Presentations" that modifies the sales process in the sales force automation system. Basically, the regional manager will now automatically be placed on the sales team for all deals that have progressed to a client presentation.
As the avenue for action becomes more automated and real-time, the organization moves closer to the highest part of the customer intelligence pyramid business activity monitoring.
Documenting Specific Decisions
By documenting decisions, companies can build a comprehensive organizational memory that enables them to quickly react to important situations and make more informed decisions. Though it may sound simple, most organizations have not spent much effort actually capturing and evaluating decisions and the knowledge around those decisions as they are made. This could be a huge cultural hurdle for some organizations.
Most organizations investing in DE technologies prompt decision-makers to document their actions after they close a given alert. The prompt usually requests specific information about the course of action, including descriptions and any attachments or links that may be relevant such as e-mails, presentations or documents that describe the course of action.
Using our example, if the sales manager chooses to include the regional sales manager on all presentations, the solution will be logged to a database and matched with the alert that was sent out. If possible, all research or decision aides (e.g., e-mails with experts, presentations, policies) can also be attached to the solution. This effort starts to combine knowledge management and document management technologies into the DE architecture.
Once the course of action is documented, the decision can be tracked and evaluated over time. Specific transactions can be associated with the decision. In some cases, these transactions can be directly attributed to the decision and, in other cases, matching decisions with transactions may be implied. The issue is very similar to identifying responses for direct marketing purposes, where an exact promotion code is not accessible requiring marketers to imply the responses from transaction data.
In our example, the sales manager should evaluate if requiring the regional manager on sales calls made an impact. His/her evaluation criterion would be to measure regional close rates for the dates after the regional manager joined (which should be stored in the application). If close rates increased, the sales manager could safely conclude that his/her decision to include the regional manager on sales calls was a success.
DE systems combine standard business intelligence technologies with knowledge management techniques and technologies to provide organizations with the ability to make decisions based on evaluating the success of past decisions.
In the end, organizations will be more proactive regarding customer-facing issues, more nimble and flexible as decisions are pushed closer to the point of customer interaction, and more accurate and swift in their responses to key issues. These qualities in the organization will also impact customer satisfaction and loyalty as organizations become more responsive and proactive.
DE is a stepping-stone to business activity monitoring, where business processes and software can seamlessly detect issues, leverage business rules and knowledge engines to research problems and proactively make changes to the operating environment. However, many organizations are not ready for the real-time and organizational impacts of BAM. DE helps bridge the gap between information display and real-time action.
The next column will discuss BAM, the state of the BAM industry and the specific technologies that enable real-time decision making.
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