Designing a Metrics Dashboard for the Sales Organization

The primary objective of the dashboard creation process is to identify and implement key performance measures and indicators that will enable managers to quickly and effectively manage the sales organization. This can be accomplished through selecting metrics that support sales objectives, strategy and goals. Some of the benefits that will result from implementing the dashboard include:

• Gain a deeper understanding of the drivers of sales productivity
• Identify where management action is required to improve sales productivity and effectiveness
• Develop a common vehicle for monitoring and improving performance
• Understand sales performance from a variety of perspectives
• Build consensus on key performance measures and drivers
• Clarify accountability around specific measures
• Enable performance benchmarking with competitors and best-in-class companies


Approach
Corporate vision guides the development of an organization’s sales objectives, strategy and tactical goals. Metrics are in turn driven by sales strategy and goals. At the tactical level, metrics serve as the primary vehicle for managing performance within the organization. Targets are set for each metric, performance is monitored and interpreted to provide timely feedback and corrective actions are initiated.

But which metrics should we choose? The sheer abundance of metrics creates a situation in which it may be difficult to properly identify metrics that make the most sense. In answering this question, the first step is to create a framework in which all the available metrics may be organized and prioritized. This framework consists in two dimensions; first, a corporate perspectives dimension and secondly a sales performance dimension. The corporate approach takes a 360 degree view of the organization from five distinct perspectives: customers, employees, partners, investors and internal processes. This approach is typically utilized in the so called “Balanced Scorecard” approach.

Each of the corporate perspectives should be examined and appropriate individuals identified to provide a list of metrics. In addition to the corporate perspective, a sales performance dimension must also be included. This breaks sales performance into four elements: readiness, productivity, efficiency and effectiveness.

Each of the corporate perspectives should be examined and appropriate individuals identified to provide a list of metrics. In addition to the corporate perspective, a sales performance dimension must also be included. This breaks sales performance into four elements: readiness, productivity, efficiency and effectiveness.

The key to the metrics identification process consists in both fact-finding and identifying metrics as well as categorizing metrics according to the above two dimensions, corporate perspective and sales performance. This basically involves the creation of a matrix with these two axes which then may be populated with metrics collected through the fact-finding process.


Dashboard Design Process
The dashboard design process consists in metric selection, design and implementation. Each of these steps involve some basic principles outlined below.

Metric Selection

• Supports stated objectives, strategies and goals
• Can be directly impacted by sales management
• Can be measured in a cost effective and timely fashion
• Reflects one of the four key dimensions of sales performance (readiness, productivity, efficiency and effectiveness)
• Enables performance benchmarking with industry competitors and best-in-class companies


Dashboard Design Principles

• Reflects senior management priorities
• Balances internal and external metrics
• Includes measures of past performance and indicators of future performance
• Minimizes the number of metrics in order to facilitate management interpretation

The actual design process is outlined below along with the detailed steps involved.

1. Metric Selection

Identify existing and potential metrics by corporate performance perspective (interview process)
• Categorize metrics into four dimensions of sales performance (efficiency, effectiveness, productivity and readiness) and eliminate unclassifiable metrics
• Create preliminary scorecard matrix that combines business perspectives with sales performance dimensions
• Review scorecard matrix for completeness and add metrics based on experience


2. Dashboard Design

• Eliminate metrics that cannot be measured or are too costly to measure
• Eliminate metrics that cannot be significantly impacted by sales management
• Prioritize metrics based on alignment with stated strategy and goals
• Select top metric per cell in scorecard matrix based on alternative approaches
• Evaluate alternative scorecards and select most appropriate metrics


3. Implementation

• Assign metric accountability
• Determine performance targets
• Obtain available benchmark data
• Determine monitoring, interpretation and feedback procedures and guidelines
• Develop corrective action review process


Metrics Matrix
Design To facilitate the dashboard design process, a matrix tool may be created to help classify the various metrics uncovered in the fact finding process. Because each metric can be understood in terms of sales performance as well as a business perspective, a metrics matrix can be created that combines the business perspectives along the horizontal axis with sales performance dimensions along the vertical axis. Each metric is placed in the matrix based on its most appropriate classification with respect to these dimensions. This tool has the following benefits:

• Creates a framework around the metrics selection process
• Balances business perspectives and sales performance views
• Provides a systematic approach
• Facilitates prioritization
• Allows identification of particular areas of emphasis
• Highlights areas with no metric coverage


Criteria for Eliminating Metrics
Eliminate metrics that cannot be measured or would be too costly to measure
• Partner coverage
• Amount of effort exerted on business approvals

Eliminate metrics that cannot be directly impacted by the sales organization
• Customer’s growth rates
• Customer profitability
• Partner satisfaction
• Number of deals involving per partner
• Share of partner revenue by platform
• Partner’s profit margin
• Partner churn
• Rate of technology transfer
• Number of certified consultants
• Number of certified partners

Prioritization Decision Rules
Each cell in the metrics matrix may contain many metrics and, as a result, must be prioritized. Some basic rules to follow in that process are as follows:

• Alignment with stated strategy and goals – Use metrics that align with strategy or show alignment with strategy the organization
• Frequency and intensity of emphasis during fact-finding – Use metrics that different corporate perspectives emphasize
• Experience – Use metrics that experience shows are important to measure
• Availability of benchmark data – Use metrics for which benchmarks exist


Preliminary Dashboard
After the completion of the matrix a preliminary matrix may be created that graphically represents the top metrics from each cell. Feedback from management can help determine additional changes or alternative metrics that are required.

Implementation Steps
After agreement on dashboard design, the implementation process may begin. Effective dashboards require live data feeds and, hence, the data integration process may be complex because of multiple data sources. Here is a list of the steps involved in implementation.

• Select final dashboard metrics
• Identify data sources
• Assess feasibility
• Assign metric accountability
• Develop action plan
• Create timeline
• Populate initial metrics
• Establish internal and external benchmarks
• Determine targets
• Determine monitoring, interpretation, feedback procedures and guidelines
• Develop corrective action review process

Best practice allows for online dashboards that may be customized to a users needs. For example, the matrix tool described above might be provided online and the user could select from these metrics those they were interested in and build up there own dashboard. In addition, each user will want the ability to drill down to a level in the organization that is relevant to their position (i.e. a district manager wants to see his district data).

In conclusion, the dashboard design process is detailed and requires thorough research. In addition, data integration and online application development are critical. However, the benefits of an effective dashboard far outweigh the costs in allowing management the critical measures necessary to guide the organization toward success.

Falconeris Marimon Caneda
Socio Director
TTS Consulting

The Agile Data Warehouse: Keeping Users Happy

Though they share a single word, agile data warehousing (DW) is nothing like agile software development.

Agile programming disciplines tend to champion a code-first, document-later ethic. Some agile approaches even eschew traditional documentation altogether. Agile programming techniques tend to place an emphasis on frequent testing: at least one agile discipline, test-driven development (TDD), explicitly prescribes a test-first approach.

In all of their variants, agile approaches emphasize the importance of frequent (and typically interactive) involvement with line-of-business customers. It isn't unusual for agile teams to solicit feedback from customers on a periodic (daily, weekly, or bi-weekly) basis. This lets them incorporate new features as customers demand them -- or change features based on feedback from users.

There are a number of reasons why a straight-up agile approach doesn't translate very well into the data warehousing world, experts say.

There's the important paradigmatic distinction between programming -- with its procedural (or line-by-line) orientation -- and data management (DM), which typically lives and thinks in a set-based world.

There are practical logistical concerns, too. "You have to look at it kind of differently, because it can take you longer to write a test case than it takes us to generate the code for you. Suddenly, you're in a different paradigm.

When you're building warehouses in an agile fashion, you're bringing together the concepts of software development and data, and a lot of the agile software techniques don't flow across to the data world."

A lot of the agile buzz at last month's TDWI World Conference in San Diego concerned agile business intelligence (BI), which, Whitehead respectfully suggests, isn't at all the same thing as agile data warehousing.

"When people talk agile in the data world, they generally talk agile BI. They generally talk about the reports, that sort of layer becoming agile. That's a no-brainer. If it's a distinct point where you have customer interaction, of course you should put something in front of them. It isn't quite so easy with a data warehouse," he argues.

All the same, Whitehead describes himself as a proponent of agile data warehousing, particularly inasmuch as "agility" connotes the acceleration or automation of tedious, onerous, time-consuming, or otherwise costly tasks.

Agility is, of course, synonymous with nimbleness, deftness -- that is, speed.

Finally, The essence of agile: "If you're a data guy, you need to make sure that you are doing whatever you can to deliver quickly and deliver value and make changes so that your stuff is relevant, If you can't do that, people are going to fill that vacuum."