Accomplishing with speed of thought
We are spoiled, want everything now, want speed, and won’t accept anything less.
Call it competitiveness. Perhaps impatience. We have a need for speed.
The evolution of files on the mainframe, to the relational database, to a cube, and the growth of spreadsheet usage along the way, innovation is borne from speed.
When it comes to line of business reporting and analytics, the same is true. The expectation is speed of thought. Meaning, you should have access to answers as quick as you think of a question. Attaining such speed provides an advantage, meaning that if my organization can act before my peers, we win.
Most organizations try to anticipate their needs and create reports to match. Generally, this approach fails. First, how can you possibly foresee every scenario of need? Second, reports come in a fixed form. More often than not, what you need can’t be found in one report.
As we’ve discussed, spreadsheets provide an important personal productivity boost. However, many business analysts create their line of business reporting by cobbling together data from multiple sources into a spreadsheet or workbook. In some cases, these spreadsheets contain a near complete replication of data from important source systems.
These spreadsheets and workbooks create quite a problem with regard to accuracy and size. First, accuracy suffers due to data replication from rekeying, copy and paste, or volume import. In addition, creating business logic and calculations in spreadsheets can be inefficient and time-consuming. All in all, these methods lack proper governance, introducing risk. Second, the greater the data volume, the larger the file. Large file size creates the greatest indication of trouble. Increased data replication yields size.
One client called their “system” BASS; an acronym for Big Ass Spread Sheet.
The opportunity to replace BASS exists in many organizations. This simply indicates a tremendous need for better analytic capability.
User consumption models
If not spreadsheets, then what?
Organizations should look develop a user consumption model. The graphic below presents user type by interactive experience. The types of user should be self-explanatory. When it comes to how information is consumed, the following five are a great place to start.
- Self-service – the ability to get what I need, when I need it, in a quick, efficient way
- Visualization – the format in which I wish to consume information; i.e. grid, chart, scatter plot, heat map, geo plot, etc.
- Dashboards – typically a fixed form view of data, perhaps displaying sets of key performance indicators (KPI)
- Published – generally, these are more report oriented and many are related to an organizations public or regulatory position; i.e. annual report, 10K, 10Q, etc.
- Narrative – text narratives are now required for many regulatory reports, creating a description or interpretation of how report details have been derived
Typical consumers are executives, managers, and analysts. Do you have additional consumers in your organization? Identify the departments to which your consumers belong. Where geographically speaking, are your consumers located?
For example, Company XYZ envisions a roll out to 1,000 users around the world. The company’s purchase of software follows the standard breakdown of users: about 80 percent are strict report consumers, 15 percent need more interaction and analysis, and 5 percent are power or administrative users. The majority of these users are in the United States, but given the global nature of the company, it is probably a 60/40 split. Do the users require 24-hour support?
Virtually every Analytics or Business Intelligence vendor provide similar features for reporting and consumption. So, choosing a vendor based upon features or functions could be tough. Selecting a vendor that provides good partnership and a solid financial status makes good sense.
When comparing functional capabilities, seek out a platform that enables great integration to transaction details, more consumption possibilities, and ease of use.
The key in all of this is simple – provide tools and create a data strategy that provides flexibility. Lack of flexibility will yield overuse and abuse of personal productivity tools like Excel and Access.
In the eBook “Having a Conversation with Data”, learn what the current BI infrastructure has been and associated challenges with the traditional approach. How important the user experience is in order to best maximize data’s value (think visualizations!!) to your organization and how to gain a competitive advantage with modern analytics platforms.