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Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects

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Delivering value is at the heart of the Business Analyst role, but how easy is it to identify tangible value and prove the success of a project or program?

In agile projects we’ll often define a “definition of done” or ask the question “what does success look like”. At LateRooms.com, we’ve developed a toolkit for our Business Analysts to support the business in using data to define what success looks like, and track it throughout the project lifecycle.

This presentation will look at the ways LateRooms.com collects, analyses and uses data to better define the problem space, setup up KPI driven Critical Success Factors and present Benefits Realisation.

Publicado en: Tecnología
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Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects

  1. 1. Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects 23rd September 2015
  2. 2. Overview  Introductions • To Jo & Jamie • To LateRooms • The LateRooms project classification model  Leveraging the most out of the data you already have  Setting up baselines and real-time KPI dashboards  Making better decisions from your data  Presenting Benefits Realisation in a way the business will understand  A LateRooms Case Study  Conclusions 2 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  3. 3. Joanne Latham – Lead Business Analyst Jo is the Lead Business Analyst at LateRooms.com where she has worked for the past 8 years. She leads the BA practice and has an intimate knowledge of the Online Travel Industry, with first-hand experience of using data to support the delivery of large transformation projects. Who are we? 3 Jamie Clouting – Principal Business Analyst Jamie is a Principal Business Analyst at LateRooms.com, with a focus on user experience and data analytics. A keen BA blogger and volunteer with the IIBA North Branch, he works with the LateRooms.com BA practice to share best-practice and mentor BAs across the wider TUI group. Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  4. 4. A little bit of LateRooms.com history LateRooms.com was born in Salford, Greater Manchester in 1999, starting life as an 'on the day for the day' booking site for unsold rooms. By 2007 we had joined the world's leading leisure travel group, TUI Travel PLC. We're still loving life here in Manchester today, now offering over 55,000 properties worldwide with more UK hotels than anybody else. Who are LateRooms.com? Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects4 And these days you can still book on the day of your stay, naturally, but also up to a whole year in advance - to make things nice and flexible for you.
  5. 5. With a lot of people who like to ‘Standup’… We work in IT 5 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  6. 6. And focus heavily on collaboration and continuous delivery We’re structured in product teams 6 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  7. 7. That focus on value and feature delivery Our work steams are expressed as roadmaps 7 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  8. 8. Leveraging value and as we go And we work on one feature at a time 8 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  9. 9. Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects 9 Leveraging the most out of the data you already have
  10. 10. But it’s siloed within departments or tools Data, data everywhere… 10 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  11. 11. Who will defend it to the death… And it has different owners 11 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  12. 12. But nobody thinks their data has quality issues And nothing lines up 12 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  13. 13. To help alleviate the pain There are a number of tools and techniques we use as BA’s to identify data within our organisations, how close it is to meeting our requirements and how accessible it is. Some of the techniques we use include: • Requirements & value analysis • Stakeholder identification • GAP analysis • Benchmarking analysis BA Activities that we undertake at this stage Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects13
  14. 14. Dust off the business case At some point in your project someone committed to some benefits that were expected. Where there is a benefit there has to be a measurement: • Higher sales • Lower costs • Greater customer retention • Improved efficiencies Requirements & value analysis Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects14
  15. 15. Who’s data is it and how can they help Data is often collected by organisations to support a number of requirements. While this data can be repurposed it may not be fit for purpose. Consider the following: • Who in your team, organisation or external to your organisation may already have data that you can use? • What was the data originally captured for and is there any restriction on its use? • Are there any data sets that could be used to support what you’re trying to measure? Stakeholder identification Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects15
  16. 16. Does the data meet your requirements or does it need enhancing? Once you have identified your data sources it’s important to work out if they meet your requirements or if they need to be enhanced to support your needs. If your data source represents a subset of the data needed you may need to decide between enhancing your data collection (if that is an option). Alternatively you may be able to combine data sets if there is a common unique attribute across both sets (however, this may be a risky strategy if the data sets get out of sync). Consider: • ROI for enhancing • How “accurate” you need the data to be • If a combined data set is reliable enough GAP Analysis Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects16 Measurementperformance
  17. 17. Don’t let the data become stale Once data is collected you should decide on a strategy to ensure it remains fresh. • Set regular reminders to review data sources • Get added to distribution lists to hear about changes in data collection projects (Business Intelligence or data warehouse updates?) • Periodically validate that the data being collected is still relevant and that it’s collection mechanism has not been superseded by an alternative means Benchmark and improve Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects17
  18. 18. Setting up baselines and real-time KPI dashboards Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects 6
  19. 19. And measure it continuously Once you have identified your data sources, stakeholders and any gaps you have in it, the next step is to give it some meaning. • Define your targets • Define your thresholds • Really good  • Really bad  • Know what happens if you breach a threshold… • Decide on measurement intervals and make sure they happen. Give your data meaning Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects19
  20. 20. ..and make sure they’re really big! Make your dashboards visible Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects20
  21. 21. Make it happen “If Engineering at Etsy has a religion, it’s the Church of Graphs. If it moves, we track it. Sometimes we’ll draw a graph of something that isn’t moving yet, just in case it decides to make a run for it.” Measure Anything, Measure Everything Make it part of your culture Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects21
  22. 22. Making better decisions from your data Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects 22
  23. 23. And allows us to manage scope • Data supports our ability to prioritise features in a much more effective way • It removes ambiguity of business benefits • It supports continuous delivery of value Data gives prioritisation context to requirements 23 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  24. 24. So we need to run some tests By generating some variants of your product you can simulate an experiment to start collecting data. This can allow us to test hypothesis’ while not risking our core KPIs. As long as you have measurement in place to identify the success or failure of a test. Sometimes the data isn’t available 24 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  25. 25. To chase value at every opportunity Traditional projects If we plan and execute our projects in this way, at what point do we know if what we delivered is the right thing? Data + Learning = Pivoting 25 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects Data driven projects Continuous measurement (and analysis) allows us to continually chase the most valuable thing next, providing organisational agility to change.
  26. 26. Presenting Benefits Realisation in a way the business will understand Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects 26
  27. 27. No more praying for good news… You know where to go and look for the success 27 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  28. 28. Good or bad, you’ve got it there… You have historical data to show the impact Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects28
  29. 29. 29 Case Study New Booking Proccess Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  30. 30. Our AS IS State • An existing booking form on a legacy technology stack that was being deprecated. • A change in Personal Card Information (PCI) regulations meant work needed to be undertaken to remain compliant. • An out-dated UI/UX that was no longer in keeping with the rest of the user’s journey. • Was not fully supported across all devices and had an adaptive approach to mobile (2 code bases). The problem Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects30
  31. 31. Document title31
  32. 32. Document title32 9 trust and confidence messages Title First name Last name Repetition (three times) Links
  33. 33. Lean UX The approach Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects33 Users Learn T Build Measure
  34. 34. Sketching & prototyping Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects34
  35. 35. Built the prototype Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects35
  36. 36. Available data Funnel reports…. Reviewing our data Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects36 Conversion rates… Missing data
  37. 37. Where are we and where do we want to be? Defined our KPIs Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects37 The problem • We had no mechanism within our BI tool that gave us a baseline of how breakfast sales performed. The solution • Implement a tracking mechanism to collect data on our AS IS breakfast sales performance. • Work with stakeholders to define a target for the next 6 months. • Set thresholds that would alert to higher or lower than expected throughput. Next • Experiment…
  38. 38. Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects38
  39. 39. Document title39 Orange = 29 Actions Green = 19 themes Yellow = Observations
  40. 40. Document title40
  41. 41. Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects41
  42. 42. Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects42 OLD FORM NEW FORM 12 6Links Links
  43. 43. Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects43 OLD FORM NEW FORM 20 12Form elements Form elements
  44. 44. A better experience for all  User experience improvements drove a conversion uplift  Benefits were delivered earlier than planned  The data helped us pivot • We never actually finished the ‘planned’ project.. • The ROI didn’t justify it.  We worked towards deprecating 2 legacy codebases  We now have a baseline of data and measurements that we can build on in the future The benefits Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects44
  45. 45. 45 Conclusions Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects
  46. 46. Wrapping it up… 1. Measuring success is linked right back to your initial requirements and stakeholder desires. You’re helping your team prove that they’ve been met with real data 2. Measuring success is a continuous process, measuring it at the end is too late… make it part of your culture 3. Measuring success continuously reduces risk and allows for innovation and agility 4. Evidence of success is the best reward of all, and will really help you as a BA Conclusions 46 Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Projects

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