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The Discipline of Business Experimentation

The data you already have can’t tell you how customers will react to innovations.<br>To discover if a concept will succeed, you must know how to proceed. <br><br>Find out more at: https://www.dtechsystems.co/resources/

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The Discipline of Business Experimentation

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  1. The Discipline of Business Experimentation

  2. Innovations Innovations D Don’t Always on’t Always Pay Pay Off. Off. Sometimes They Fail Spectacularly.

  3. Big Big Data Has Data Has It’s Limits It’s Limits It can’t always predict the future.

  4. Innovations Innovations Need A more reliable way to evaluate new initiatives. Need Rigorous Rigorous Testing Testing

  5. A RIGOROUS EXPERIMENT Relies on proven scientific and statistical methods. Has a sample size that will yield valid results. Tests one independent variable against a dependent variable while holding all other variables constant. Incorporates careful observation and analysis. • • • •

  6. Five Keys to Five Keys to Good Experiments Good Experiments Purpose Buy-In Feasibility Reliability Value

  7. #1 #1 Does the E Does the Experiment xperiment H Have a a Clear Purpose Clear Purpose? ? ave Start with a Strong Hypothesis Avoid if the Hypothesis results are weak • •

  8. #2 #2 Have Have Stakeholders Agreed Stakeholders Agreed to Abide by to Abide by the the Results? Results? Weigh All the Findings Walk Away if They’re Negative • •

  9. #3 #3 Is Is the the Experiment Experiment Doable Doable? ? Potential Roadblocks Too Much Complexity Costly Sample Size Operational Disruptions • • • •

  10. # #4 4 How Can We Ensure How Can We Ensure Reliable Results? Reliable Results? Randomized Field Trials Blind Tests Big Data • • •

  11. #5 #5 Have Have We Gotten We Gotten the Value out Value out of the of the Experiment the Most Most Experiment? ? • Invest in areas where the ROI will be highest. • Determine which components have a positive return.

  12. It All Comes Down It All Comes Down to to Rigor Rigor Purpose Buy-In Feasibility Reliability Value

  13. Experiment Experiment Checklist Checklist Purpose • What specific management action are we considering? • What do we hope to learn? Buy-In • What specific changes will we make on the basis of the results? • How will we ensure that the results aren’t ignored?

  14. Experiment Experiment Checklist Checklist Feasibility • Do we have a testable prediction? • What sample size do we need? • Can we avoid disrupting operations at the test locations? Reliability • What measures will we take to counteract bias? • Would others conducting the same test obtain similar results?

  15. Experiment Experiment Checklist Checklist Value • Can we do a targeted rollout focusing on areas where the payback is highest? • Have we implemented only the components with the highest returns? • Do we understand which variables are causing which effects?

  16. Thank You You can contact us at 00966 56 100 4748 info@dtechsystems.co www.dtechsystems.co

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