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The Analytics Lifecycle

  1. 1. by Simon Harrison, Operations Director 13th September 2019 The Analytics Lifecycle
  2. 2. Quick Bio Simon Harrison - Operations Director at DeeperThanBlue Analytics Ltd Qualifications • ACMA - Associate Chartered Management Accountant Experience • 1 year at DeeperThanBlue as Analytics Director • 10 years at Sports Direct to Head of Financial Planning and Analytics £3Bn T/o • 10 years at Morrisons PLC to Head of Finance for a £300m Food Manufacturing Subsidiary Skills • Management Accounting, Budgeting, Planning, Forecasting • Performance Management, Business Analysis, Business Analytics • TM1, SQL, ODBC, Strong Excel, Cognos, SPSS, Watson Data Studio
  3. 3. Away from Work Junior Football Team Manager Kiveton Park FC – Under 13s Level 1 FA Coach 12 year old son – played since he was 5 9 year old daughter – played since the ladies world cup
  4. 4. About DeeperThanBlue Analytics • We are a Sheffield based IBM and Microsoft business partner with competencies in Business Intelligence, Financial Planning, Performance Management, Predictive Analytics. • Supporting a wide variety of clients across a broad range sectors including retail, logistics, manufacturing and distribution. • We offer a full end to end service, from initial design concept through to implementation, consultancy and on-going support either on- premise or on cloud (or both). • To find out more please click www.deeperthanblue.co.uk/solutions/analytics/
  5. 5. Introduction The aim of this session is highlight the benefits that analytics can bring And how I believe Finance are ideally placed to enable change by being centrally positioned The presentation will be shared after the event
  6. 6. Advanced AnalyticsTraditional Reporting & BI The Analytics Lifecycle Descriptive Analytics What happened? Basic understanding of results, accurate, relevant timely data Value v Complexity Value Complexity
  7. 7. Advanced AnalyticsTraditional Reporting & BI The Analytics Lifecycle Diagnostic Analytics Why did it happen? Understanding what caused an outcome Data exploration Value v Complexity Value Complexity
  8. 8. Advanced AnalyticsTraditional Reporting & BI The Analytics Lifecycle Predictive Analytics What will happen? Statistical analytics techniques to uncover patterns in the data Value v Complexity Value Complexity
  9. 9. Advanced AnalyticsTraditional Reporting & BI The Analytics Lifecycle Prescriptive Analytics What shall we do next? The optimisation of outcomes subject to constraints Value v Complexity Value Complexity
  10. 10. What is it? The process of turning raw data into meaningful information Dashboards, Reports, Visualisations, Business Intelligence How does it help? Visual representations e.g. charts are readily understood Information is easily distributed and controlled Useful to give real-time information on mobile platforms Product examples IBM Cognos Analytics, Microsoft PowerBI, Tableau, Qlik SEE with Descriptive Analytics
  11. 11. SEE WHY with Diagnostic Analytics What is it? Diagnostic Analytics is the next level of advanced analytics, the purpose is to identify not what happened, but why. Diagnostic analytics is designed to help find answers to what caused or contributed to an end result. How does it help? Business Intelligence tools that enable diagnostic analytics have features such as data exploration, data mining and correlation. Cognos Analytics 11.1 delivered a strong improvement in these capabilities Product examples IBM Cognos Analytics (Formerly Watson Analytics)
  12. 12. PREDICT with Predictive Analytics What is it? Advanced analytics that uses statistical techniques and data mining methods to find insights which may be overlooked by BI methods The foundation of machine learning How does it help? The ability to dig deeper into relationships within the data will find new drivers of value, allowing new opportunities to be found Product examples IBM SPSS, IBM Watson Studio Seasonality Growth
  13. 13. AUTOMATE with Prescriptive Analytics What is it? Prescriptive Analytics is designed to calculate the best solution to complex problems that can have a range of different options to take. How does it help? An example of this may be a retailer planning its staffing levels, but taking into account shift patterns, skill levels, and other constraints. Prescriptive Analytics is used to find the optimum solution Product examples IBM ILog CPlex
  14. 14. PLAN with Planning Analytics IBM Planning Analytics What is it? Integrated business planning allows co-ordination of departmental budgets and forecasts Scenario planning, reporting and KPI monitoring and Excel integration A.k.a CPM, EPM, FOPM How does it help? Co-ordinated workflows allow true connected planning, collaboration and goal alignment, with built-in monitoring and reporting Product examples IBM Planning Analytics, Adaptive Insights
  15. 15. Planning as the Central Control Point IBM Planning Analytics The plan as the central point naturally reflects the position of the finance team from an information and control point of view As analytics becomes ever more capable, it becomes increasingly important to feed the insights back into the planning process to ensure value is delivered Then well established variance analysis methods can be brought into play to help the business understand the variances and make required corrections Plan See - Descriptive Why - Diagnostic Predict - Predictive Automate - Prescriptive
  16. 16. Advanced AnalyticsTraditional Reporting & BI The Analytics Lifecycle Where are you on the journey? Value v Complexity Value Complexity
  17. 17. Understanding the Journey Moving from Financial to Operational to External (Big Data) External Data (Big Data) Operational Data Financial Data Complexity Value
  18. 18. Impact on Accounting Skills required to stay current
  19. 19. Impact on Accounting Skills required to stay current Curiosity
  20. 20. Impact on Accounting Skills required to stay current Curiosity Understanding the business
  21. 21. Impact on Accounting Skills required to stay current Curiosity Understanding the business Relationship Building
  22. 22. Impact on Accounting Skills required to stay current Curiosity Understanding the business Relationship Building Resilience
  23. 23. Impact on Accounting Skills required to stay current Curiosity Understanding the business Relationship Building Resilience Effective Communication
  24. 24. Impact on Accounting Skills required to stay current Curiosity Understanding the business Relationship Building Resilience Effective Communication Never settle
  25. 25. Impact on Accounting Skills required to stay current Curiosity Understanding the business Relationship Building Resilience Effective Communication Never settle Technology Understanding
  26. 26. • Trial and error can be very useful • Start small and build on quick wins • Involve people on the ‘journey’ • Explain errors / anomalies • Build continuous improvement, track performance • Discuss assumptions, fall back positions • Tailor for the end user • Focus on achieving value • Build connected follow on projects Lessons Learned
  27. 27. Q&A Questions
  28. 28. Find out More Business Analytics forum Next one coming up in November, going on the road, likely to be Manchester first The theme will be around Planning Analytics and decision optimization, with some great speakers Dates to be released next week https://www.deeperthanblue.co.uk/business -analytics-forum-3-4th-july-2019/
  29. 29. Contact details: simon.harrison@deeperthanblue.co.uk +44 (0) 7949 763 848 https://www.linkedin.com/in/simon-harrison-dtb/ Thank you, if you would like any further details or advice please get in touch! www.deeperthanblue.co.uk
  30. 30. Understanding the Terminology Description of key terms

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