12: The Right Tool for the Right User
The chapter begins with an anecdote from Dow Chemical, which sought to implement a "global reporting" tool in 1994, ahead of vendor solutions for BI, and met with "resistance on all sides" from users who found the tools too difficult to use, departments that clung to the reporting formats they were getting from older systems, etc. and ultimately were unable to get adequate buy-in from anyone outside the IT department and logistics. The example illustrates two fundamental mistakes: the failure to get sufficient input when selecting a solution, and a failure to build consensus along the way.
The Importance of BI Tools
While IT departments focus on the back-end systems that handle the data, the business users focus their attention on the front-end tools that provide the access and functionality they need. No matter how well the back-end is executed, BI will fail if the front-end tools to not suit the needs of the users.
While business users do not entirely ignore the back-end, the focus on their concern is the value it delivers: the back-end must support the user tools by providing accessible, high-quality data. The study findings suggest that business users will tolerate some degree of reliability in exchange for better tools.
The Role of BI Standardization
The value of standardization to vendors is in having a package solution that can be sold to multiple clients; and the value of standardization to IT departments is the ready availability of documentation, support, and the ability to hire pre-trained personnel. However, this tends to lead to the adoption of off-the-rack solutions that ultimately fail because they do not suit the needs of the business.
Internal standardization, however, is of high importance, in that the data available and analyses performed muse be common within an organization, providing users with information that will be commonly accepted across the organization (rather than each department coming to the table with different information). But even that can be taken too far: in that a single set of standard reports and tools will not be useful for all departments: hence users will need access to different dashboards, reports, and queries that suit their needs.
Problems can arise when companies take a multi-vendor approach to their enterprise BI systems: while various vendors have competency in certain areas, and can serve the needs of some components of the business, this comes at a cost of redundancy, duplication, and inconsistency in interpretation, which should be addressed on the enterprise level.
Contrary to the obvious conclusion (developing custom tools that are internally standard), the author's survey found that companies that use a single-vendor solution report the highest level of success with their BI systems than those that custom solutions. It's also noted that 75% of companies switch BI vendors during the course of their deployment, citing various reasons, such as licensing costs, vendor complacency, and the rigidity of the solution.
The Right Tool for the Right User
A common mistake in considering BI is in an attempt to define a standard toolset to be provided to all users, as if they had the same needs. A senior executive and a sales representative have different functions, hence different needs, and it doesn't merely apply to the "level" of data analyzed, but to the analysis itself. A better approach is to segment the user base into groups with similar characteristics, needs, and desired benefits.
The author describes some of the key characteristics that identify a BI user segment:
- The frequency and nature of fact-based decisions. The "nature" is divided into strategic, tactical, and operational, reflecting the degree of impact and breadth of horizon.
- Whether their needs are predictable. Generally, individuals with routine duties in a specific area of expertise, their needs are limited and predictable
- Job level - The lower the user's job level, the narrower the scope of the data they will require. However, it's to be noted that the front-line worker has significantly different analytical needs, not merely a more tightly-focused version of data.
- Job function - Employees in finance, marketing, manufacturing, logistics, and other functional areas of a company have specific needs, though the needs of one department may be impacted by the data that seems relevant to another (e.g., production is often driven by sales predictions).
- Degree of analytic job content - Certain jobs entail a significant amount of data analysis in order to make competent decisions or undertake meaningful actions. They may need access to real-time data rather than periodic, and they may need different tools for customizing the way in which the information is analyzed.
- Technical literacy - The level of a user's technical literacy, particularly in the use of spreadsheets and databases, will influence the degree to which analytical tools are needed. Some users can best be served by exporting data from the systems, others will need graphical representations that do not require calculation or analysis. This is one area in which BI systems may overwhelm some users, leading them to abandon the intelligence and resume gut-feel decision making behaviors.
- Data literacy - Data literacy is different from computer literacy. For example, a savvy computer user may not be able to derive meaning from information he does not understand. For example, production managers may not understand the subtle nuances of revenue, nor may financial professionals be able to fathom information related to production.
- Environment and Travel - The physical environment of a user may determine which BI tools are of the greatest use to them. An executive who travels frequently may have a need for information to be accessible via a mobile device.
- External Users - There is also a need for information to be shared with external customers and suppliers. Generally, this requires more restrictions on content, but providing access to certain data facilitate self-service and utilization for customers and increase the efficiency of the supply chain when provided to vendors.
The Most Successful BI Module
Across the body of survey respondents, there was one tool that was most frequently used by successful BI deployments: Microsoft Excel. Contrary to the level of hype given to "dashboards" and predictive analytics, the most successful BI implementations rely heavily upon ad-hoc query capabilities that provide data tables that can be loaded into Excel for more detailed and unconstrained analysis.
There are, however, some drawbacks to integrating BI systems with Excel. A few problems listed include inaccurate data being fed to spreadsheets for analysis, a simple spreadsheet error can result in incorrect analyses, and enabling employees to download spreadsheet data to laptop computers may be a security risk (if the laptop is stolen and the data is not properly encrypted).
In spite of these problems, respondents to an informal poll at an event indicated that a large percentage of BI users (67%) indicated that more than half of their reports are routinely exported to Excel, and follow-up polls at other events have been largely consistent with this ratio.