Adding Value to Business Intelligence

Adding Visual and Metric Value to Business Intelligence

New Visualisation Styles for Multi-Dimensional Data and Time Series


This article is based on

  1. Best Business Intelligence Software[1] – by G2Crowd[2]
  2. The Top 15 Business Intelligence Software Report[3] – by[4]
  3. The 54 Best Business Tools[5]: Top BI Software to Help You Analyze Data to Make Smarter Business Decisions.

The Report Summary of G2Crowd[6] echoes other reviewers’ conclusions:

  • Low user adoption – possibly due to difficulties in ease of administration and setup;
  • Users enjoy visuals – reports, graphs, charts, dashboards, data visualisation and metrics are valued;
  • Satisfaction ratings have increased – but the ease of doing business has not!

Our Features of Distinction

At its lowest level, 3d metric visualisation styles[7] become third party implementations of our Smart Knowledge Engine[8]:

  • to unclutter Excel charts by layering dimensions[9];
  • to forecast time series[10] and determine past and future short-, medium- and long term-trends;
  • to re-visualise images[11] for more depth, detail and structure – which applies mainly to the health, materials and science sectors, but also the automotive and other industries, where the quality of surfaces matter.

As a data analytical environment, we will produce a Visual Data Operating System[12] with Smart Data Portals[13], where the selection of structured data and images is an essential part of categorisation and visualisation – with the purpose of comparisons over time.

For ‘visualisation’ is the engine we want to drive with ‘data’ as the new fuel – by selecting horses for courses:

  • company internal vs external data
    • for policy and leadership vs marketing and outreach;
  • structured vs unstructured data
    • for numbers and statistics vs words and interpretations;
  • past and future trends
    • as the visual measure of developments
    • with financial trends as the yardstick for making decisions.

Comparing Time Series Visually and Numerically

Time series can now be compared in new ways:

21 series of 3 pollutants in air quality data The same data as 21 ‘layers’ along ‘visual z’ The layers sorted for prioritisation

Data shown by Excel
Eleven Layers of sine values in Excel The same data as a ‘3D object’ along ‘visual z’

Similarly, our decisions ought to be based on the same kind of information, updated over time, as we observe their impact and effects.

The initial selection of key data is thus as critical for executive summaries as the ability to drill down and zoom in on shorter time periods or particular aspects of business operations.

Microsoft Power BI

The titles of sample data show that the analytical thinking does not go as deep as mine which looks generically at numerical series of RAW data for CONTENT analysis over TIME – rather than any interpretation such as ‘profitability’ or ‘quality’:

  • Customer profitability sample
  • human resources sample
  • IT spend analysis sample
  • Opportunity analysis sample
  • Procurement analysis sample
  • Retail analysis sample
  • Sales and Marketing sample
  • Supplier quality analysis sample.

Bottom lines are cash flow and profit as the yardstick with which all other trends need to be compared for Board Room summaries.

In contrast, ‘market share’ and ‘sentiment’ are external considerations that should only be taken into account, once all problem areas have been addressed internally.

Too many detailed reports and too many apples are being compared with oranges, in my view.

Clarity for Comparisons

Finding not just compelling, but also comparable data is the task! And data that tells the story we want to hear!

But to do better, we may have to use a real live company to demonstrate:

  1. Data selections
    • With the reason of investigation: quality / efficiency / effectiveness / profitability.
  2. Data comparisons
    • With the purpose of comparison: branches / departments / products / costs / losses.
  3. Trend visualisations
    • The most meaningful view for comparing the development of individual processes that shape the future of the collective activities of a company: short-, medium- and long-term.




[3] file:///C:/Users/Sabine%20K%20McNeill/Downloads/17%2008%2017%20top_10_bi.pdf