The Past, Present, and Future of Business Dashboards

Written by Kally Pan on Aug 11, 2016

Business dashboards are rapidly becoming an integral part of businesses today. The ability to provide accurate data on the state of the company to business users has made them vital to any data driven decision-making process.

While the idea of using data and metrics to power iterative and optimized business decisions has become a mainstream, the root of the idea is not new. Here, we take a look at where the modern business dashboard concept comes from, where it is today, and some thoughts where it might go in the future.

Background: Business Data Analytics

Keeping business records has existed since the beginning of civilization with origins around the time that humans first began to count. Much of the earliest archaeological evidence of writing are of records of business transactions and inventory data for the keeping of grain and foodstuffs. In fact, there is strong evidence that many of the earliest advances in math, such as the concept of zero, arithmetic, and fractions were made to deal with business tractions and trade. The people who produced this work were the elites of the society and their work was seen as mysterious and incomprehensible by the common man.

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Wait, this cuneiform formatting is all wrong!

However, analyzing business data at a scale that would enable patterns and insights did not become practical until the rise of computing. Around World War 2, mechanical devices were complex enough to perform calculations at speeds that greatly surpassed humans. The War itself created the first computing systems – RADAR guided battleship guns – that turned calculations into practical information. However, all of these use cases were specialized and heavily concentrated in government and the military. It was the invention of the solid state transistor that made it practical for the implementation of information systems in business.

Executive Information System

The 80’s saw the creation of the Executive Information System (EIS), the first integrated system that resembles a modern dashboard. It combined graphical displays, easy to use UI, and strong reporting and drill-down capabilities so that top-level executives could analyze data and discover trends while monitoring performance.

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Wait, this spreadsheet formatting is all wrong!

These systems came as a package with mainframes, dedicated software programs, even dedicated telecommunication networks and were typically only able to provide data that supported C-level decisions. Their price and limitations in terms of data made them available only to elite leadership at the largest corporations. However, it was already clear that the benefits of having such a system empowered business users to create stronger strategies and make better decisions.

Business Intelligence Systems

As the value of data driven decision making was validated for top level executives, the EIS lead to the development of Business Intelligence (BI) systems, which attempted to bring the benefits of EIS down the corporate ladder. To service the needs of a much wider audience, there was a much larger emphasis on data warehousing and the development of support processes. Likewise, the functions of BI systems were also increased to include data mining and processing, historic and predictive analysis, and complex event processing.

BI is built around data and requires a more comprehensive collection and centralization of business data than previous systems as it attempts to gain a greater holistic look at all the data generated by a company. The scale of the operation demanded not only more sophisticated technology, but also greater usability as the greater number and variety of users required a system that is more intuitive to use while being tailored to their missions at the same time.

Business Performance Management

The complexity introduced by heavy weight BI tools, required a set of processes that would retrain managers to make the most of these tools. Business Performance Management (BPM) eventually evolved to help managers to selection goals, create KPIs to track progress, and provide analytics to help iterate on performance so goals can be reached faster. Typically, this also required abilities to communicate strategy across an entire organization and to enable a greater degree of collaboration within teams. However, the wider application of data within organization created much stronger results, often transforming the entire culture of companies and lead to the push for greater transparency, flatter and more flexible management, and leaner, stronger companies.

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Wait, this Excel formatting is all wrong!

The creation of EIS, BI, and BPM was sequential but each system was additive, improving on the benefits of the old while introducing both new functionality as well as a wider user base. The great synthesis of these parts resulted in the business dashboards as we understand them today. Properly used, dashboards can serve as a platform to:

Communicate strategy – translate into concrete measurable goals
Refine strategy – allow iteration by shifting targets
Increase visibility – bubble relevant data to management
Increase coordination – allow information to flow across organizational or structural borders
Increase motivation – encourage friendly competition
Consistent view of the business – create single source of truth (comment definitions, rules, and metrics)
Reduce cost and redundancy – consolidate data and reduce duplication of siloed data
Empower users – reduce reliance on IT or outside help for customizing reports
Deliver actionable information – relevant data at the right time allows corrective action
[*excepted from Performance Dashboards by Wayne Eckerson]

The Future

The power, scope, and scale of both technology and data collection has been growing exponentially. The potential for business dashboards is sky high. Business dashboard tools in the future are likely to incorporate machine learning and AI so they can bubble up points of interest and identify patterns in raw data that even the most well equipped data scientist will not be able to find manually.

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I for one, welcome the formatting of my A.I. overlords.

It’s clear that there’s a trend in bringing wider access to more people as well as to organizations previously too small to use legacy systems. Moving forward, balancing access with functionality will be the challenge facing the industry.