A barrel of schnapps, an incompetent leader and business analytics

What do these three things have in common? They help illustrate the four steps for creating a measurement framework

Business analytics is about doing things better. Unfortunately, success isn't always enough – if you can't define, communicate or measure the value you're creating, it can be surprisingly hard to convince people of the value of business analytics. Communication is key, and miscommunication can cost you dearly.

One of the best examples is the somewhat absurd story of Joseph II: On Sept. 20, 1788, more than 10,000 men were killed or wounded because of a barrel of schnapps, an incompetent leader and the lack of a common vocabulary.

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Evan Stubbs, SAS

The sad story of Joseph II

Joseph II, emperor of Austria, had a burning desire to go down in history as one of the world's most astute military leaders. Unfortunately, he lacked any talent whatsoever. In his crusade to liberate the Balkans from the Turks, he suffered one of the most inglorious defeats in military history.

It was a dark night when his cavalry vanguard arrived at Karansebes. They didn't find any Turks, but they did find a troop of happy Walachians with schnapps to spare. Shortly afterward, Joseph II's infantry approached and demanded their share of the alcohol. A fight broke out and the infantry shouted, "Turci! Turci!" to fool the others into thinking the Turks were attacking.

The ruse worked, and Joseph's cavalry fled. Unfortunately, the infantry's shouts were so convincing that the foot soldiers opened fire in earnest, emptying their rifles into the dark at the non-existent Turks. Their officers tried to gain control of the situation, but Joseph II had recruited broadly, and his largely non-German-speaking troops couldn't understand the officers' commands.

As a result, the small altercation devolved into total chaos, and by the end of the night Joseph II had fled for his life. When the Turks arrived two days later, they found an abandoned campground, 10,000 dead or wounded troops, and no Joseph II.

Learning from Joseph's mistakes

Like Joseph II, business analytics practitioners want to change the world around them. Joseph II succeeded, but not in the way he would have liked. We remember him only as an important lesson in what not to do. His self-created defeat at Karansebes might have been avoided had he:

Had a clear vision of where he was going.

Made sure his team was speaking a common language.

Know where you're going

When initiatives and projects can't be mapped to the creation of value or competitive advantage, it means business analytics managers and data scientists don't have a clear vision of where they're going, they can't explain how their work is contributing to the bottom line, and they are spending significant amounts of time on things that may or may not be important.

For Joseph, one of his downfalls was a largely futile and misdirected war against the Turks. For business analytics managers, it's often chasing projects that are too large, have no clearly defined outcomes, or require competencies and assets that haven't yet been developed.

Having that road map is critical. By understanding and being able to explain how every activity and project creates value and leads to a point of true strategic differentiation, the business analytics team changes from simply delivering operational efficiencies to becoming a focal point for organizational success. While it's often overlooked, business analytics is about organizational transformation. Having a vision and a road map that explain how that transformation will occur is key to making it happen.

Speak the same language

Having a road map is essential, but it's not enough. As Joseph II discovered, things fall apart when everyone is speaking a different language. Establishing a common measurement framework does two things:

  • It makes it easy to compare results and benefits between very different projects.
  • It establishes a common vocabulary for both the team and the organization.

Every change can be measured in one of three ways:

  • Business measures help identify changes to outcomes and demonstrate the ability of business analytics initiatives to create value.
  • Analytical measures help identify changes to the assets the team works with and streamlines team activity by focusing attention where it's needed.
  • Technical measures help quantify the effort needed to achieve an outcome and define where optimization activities need to occur.

By defining a common measurement framework, data scientists can compare different initiatives against each other. And having a common and standard vocabulary makes it easier to communicate their value to the organization.

Four steps for creating a measurement framework

A measurement framework will keep your team focused and prevent wasting time on activities that don't add value. Getting started is straightforward. Just follow these four steps:

  • Identify the measures: Understand what's important to both your team and to the broader organization.
  • Make it real: Establish a platform to support visualization and management by exception. Use dashboards, alerts and workflows so that if something goes wrong, you know it immediately.
  • Automate it: Make sure the measures are automatically generated – the systems themselves should have the ability to track response rates, calculate return on investment, and profile time and effort needed to complete various activities. Every second spent manually updating this information is time that could have been spent actually creating value.
  • Optimize, improve and promote: Use these measures to justify the value being created and target optimization activities.

Joseph II's story ended badly. Dying a broken man in 1790, he asked that his epitaph read, "Here lies Joseph II, who failed in all he undertook." However, his mistakes are our lessons. While we may not be trying to unite Europe, we too have a vision for changing the world – by changing the way we do business.

Bio: Evan Stubbs is the regional product manager for analytics at SAS Australia/New Zealand and author of The Value of Business Analytics.

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Your checklist for identifying measures

  • What business, analytical and technical measures need to be tracked?
  • How would each measure be quantified and captured?
  • Who would find these measures useful and valuable?
  • How will capturing these measures be automated?
  • How will these measures be reported?

Adapted from The Value of Business Analytics, 2011, Evan Stubbs.


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