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Softer Skills workshop for #DTS16 event in Edinburgh


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Slides presented as keynote workshop at Data Talent Scotland 2016 event, brining together Data Science students, academics, employers & data industry for conversation & talent pipeline.

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Softer Skills workshop for #DTS16 event in Edinburgh

  1. 1. Paul Laughlin, Managing Director, Laughlin Consultancy The Softer Skills Data Scientists also need to make an impact in business
  2. 2. Career within Lloyds Banking Group ❖ Created & lead customer insight teams for all the major insurance brands, products & channels used by Lloyds Banking Group over 13 years ❖ Added over £11m incremental profit to bottom line annually ❖ Pioneered work with Financial Conduct Authority on Behavioural Economics in communications ❖ Developed capability in team of 44 & mentored next generation of leaders
  3. 3. Helping Businesses “Helping businesses make money from customer insight” Laughlin Consultancy helps companies maximise sustainable value from their customer insight, for example by growing their bottom line, improving customer retention and demonstrating to their regulator that they treat customers fairly.
  4. 4. Data Science at the Whitehouse
  5. 5. 9 Step Analysis Model
  6. 6. Breadth not Depth
  7. 7. Getting a better brief Question
  8. 8. The problem with requests
  9. 9. Socratic questioning ❖ Aim is to help client have clarity on need not just what they want: ❖ Concept clarification questions ❖ Probing assumptions ❖ Probing rationale, reasons & evidence ❖ Questioning viewpoints & perspectives ❖ Probe implications & consequences
  10. 10. Failing to Prepare is preparing to Fail 11 Question Planning & Design
  11. 11. Design Map What do we already know? What am I missing? How could I fill this gap? How am I going to communicate findings? What are the Hypotheses? You could start at any point in the cycle but you should look to address all elements in completing your analysis
  12. 12. Who Use / Involvement / Experience Shopping/Buying Engagement / Influences▪What characterises the customer/ segment −demographics −stage of life −attitudes −behaviours −dissatisfactions −routines −etc ▪What are their chief concerns in life (attitudinal data)? ▪What are their key needs and aspirations? ▪What are their circumstances and what is going on in their lives that impacts how they see the category? ▪What motivates them? ▪ What are their preferred channels for researching and purchasing products and how does this compare with other types of products? ▪ How do they make a purchase decision and what factors are important? ▪ What are their attitudes to advice? What prompts/triggers them to seek advice? ▪ How do they perceive your brand vs other brands? (product category and wider) ▪ How do they become aware of the category? ▪ What is there attitude to planning for the future? When do they think ahead, what triggers this? ▪ When do they reconsider their choices? What prompts change? ▪ What and who influences them and their choices? Who do they turn to for guidance/information/ recommendations? ▪ What competitive product holdings do they have and why? ▪ When are they receptive to messages? ▪ What does the segment need and want when buying your products? ▪ What products are they most likely to buy and why? ▪ What is the current customer experience? ▪ What are the key dissatisfactions (irritations, frustrations etc) with the current process? Pricing/Finances ▪ How engaged/informed/involved are they with regard to competitive pricing? ▪ What products do they hold? How does this contrast with other segments? ▪ What triggered their purchase? What stops them buying? ▪ Do they go on to buy something else? (us or competitor) ▪ What are their goals and to what extent do they plan their spend (budgets)? Context questions
  13. 13. Achieving Stakeholder Buy-In 14 Question Planning & Design Buy-in
  14. 14. Stakeholder Mapping
  15. 15. Technical stages (Data & Analytics) Question Data Analysis Insight Planning & Design Buy-in
  16. 16. Generating Customer Insights Question Data Analysis Insight Planning & Design Buy-in
  17. 17. Converging sources of evidence
  18. 18. Agreeing Sign-off and Tactics Question Data Analysis Insight Planning & Design Buy-in Sign-off
  19. 19. Communicating your analysis effectively Question Data Analysis Insight Planning & Design Presentation & Distribution Buy-in Sign-off
  20. 20. Hierarchies of communication ❖ Hierarchies of headlining ❖ Short, eye-catching, wording
  21. 21. Storytelling ❖ People are engagedby stories ❖ Psychological studies show better attention & recall (esp. feelings) ❖ Common templates: ❖ “Just imagine, if…” ❖ “Wow! I’m going to tell… about this” ❖ The Burning Platform
  22. 22. Tufte’s rules for Data Visualisation ❖ Graphical integrity ❖ Data-Ink ❖ Chart Junk ❖ Data Density ❖ Small Multiples
  23. 23. Negative examples of Data Visualisation
  24. 24. Checkout Viz.WTF
  25. 25. Positive example of Data Visualisation
  26. 26. Influencing the Action needed as a result Question Data Analysis Insight Planning & Design Presentation & Distribution Solution Buy-in Sign-off
  27. 27. It’s all about taking Action ❖ Ensuring request is for action ❖ Designing analysis for action ❖ Including recommended actions ❖ Progress updates on action ❖ Measure effect of actions
  28. 28. 9 Step Analysis Model
  29. 29. Our Exercise = Back to Socrates Concept Clarification: ❖ What exactly does X mean? Can you give an example? Probing Assumptions: ❖ You seem to be assuming Y, please explain why? Probing Rationale: ❖ What evidence is there to support what you are saying? Questioning viewpoints & perspectives: ❖ Another way of looking at this is Z, is that better?
  30. 30. 9 Step Analysis Model
  31. 31. Action orientated learning One thing I will do differently as a result of this presentation is…
  32. 32. +44 (0)7446958061 How to keep in touch @LaughlinPaul