- Tier 1: Business Metrics — Are we contributing to profitable revenue growth?
- Tier 2: User Productivity — Are we impacting the user productivity?
- Tier 3: IT Productivity — Are we more efficient in our IT operations?
In this post, I want to expand on what I mean by user productivity.
Who are BI and analytic users
- All size organizations from every geography use some type of BI in decision-making
- BI and analytic solutions are being integrated in operational systems and processes and trigger automated decisions
- All levels of the organization and external parties use BI and analytics
- Board of Directors and Chief Executive Officers are hands-on users (direct use) or receive the results from someone else in the organization (indirect use)
- BI and analytic results are shared with customers and suppliers.
Why are they using BI and analytics
Figure 2 Software Usage Subjects & Methods
- Allocation or reallocation of responsibilities or resources
- Forecasting or predicting the most promising strategic options
- Customer mix, competitive emphasis or organizational structure
- Setting the financial land non-financial goals of the organization
- Implementing annual Objectives or short-term strategies
- Individual business unit objectifies and strategies
An United States financial services company that used a financial planning and analysis solution to maintain earnings before tax and interest in the mid 20 percent range and increase revenue by 250%.
An Iranian agency selling cable and related technology was able to add capabilities to predict material cost, transportation and delivery, exchange rate, and other values before making offer. The result was higher profits and improved coordination with suppliers.
A Kenyaian insurance company was able to deploy BI capabilities to its agents resulting in a being able to close policies within the same day and at the point of sale. They were also able to move into new business markets such as micro-insurance.
A “New Europe” telecommunication company that deployed data mining technology for a wide selection of customer and product decisions, including customer profiling and tariff simulations. The result was a reduction in decision cycles from weeks to days.
What are some tier 2 measures
Table 1 Tier 2 BI & Analytic Measures — User Productivity
Why is it hard to meet user needs
- Large number of data sources
- Growing volumes of data
- Need for structured and unstructured data
- Decision time windows are shrinking
- Lack of skilled resources
- and, and and …
Some ideas for consideration
- Engage management…we are in fact talking a culture of fact-based decisions. Incremental changes can occur without management seeing BI and analytics as a core competency, but much more can happen when they are fully engaged
- Establish an entity responsible for supporting decision-making; our research has shown that organizations with a BI compentency center (or similar) have a higher correlation between BI and improved organizational performance
- Build communities of practice that share experiences and ideas on using BI & analytics
- Automate and standardize the creation of routine reports and information
- Provide a selection of different reporting and analytical tools that fit to the different type of user profiles
- Provide options and different environments for working with different types, quality, and volumes of data
- Provide options for different user profiles to have access to different levels of computing power
- Use agile methods for developing BI and analytical solutions
- Consider SaaS solutions. support and encourage users to find niche applications that serve their need. help them with interfaces and agreements– be sure you will own the data.
- Employ some new technologies e.g., visual analytics, in-memory analytics, data warehouse appliances
- Miller, Gloria J., Queisser, Thomas, Goettsche, Thomas. Mobilizing Technology and Teams for Better Decision Making, May 2011
- White, David. Agile BI: Three Steps to Analytic Heaven. AbeerdeenGroup, April 2011
- White, David and York, Matthew. Agile or Fragile? Your Analytics, Your Choice. AbeerdeenGroup, July 2012
- Stoddler, David. Achieving Greater Agility with Business Intelligence.Â TDWI Best practices Report, TDWI Research, First Quarter 2013.