1. www.reportinghouse.com Leveraging Maximo data to increase Asset effectiveness & ROI through Analytics Presenters: Samir Vyas, Director, Business Development Pankaj Shetye, Sr. Project Manager

2. www.reportinghouse.com Agenda 1.Data explosion in Maximo 2.Business Analytics – What is it? 3.Growth of Analytics 4.Common Statistical techniques used in Analytics 5.Challenges of doing Analytics 6.Readiness assessment questionnaire 7.Strengths of Maximo data 8.Success factors 9.Business Use Cases in Maximo 10.Interactive discussion

3. www.reportinghouse.com Data Explosion in Maximo

4. www.reportinghouse.com Business Analytics

5. www.reportinghouse.com Business Analytics … defined Business analytics refers to: the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Source: Wikipedia

6. www.reportinghouse.com Growth of Analytics

7. www.reportinghouse.com Common Statistical techniques used in Analytics Weibull distribution Regression Analysis Time Series Exponential Smoothing Clustering Decision Tree Pareto Analysis Control Charts Histograms Trend Analysis

8. www.reportinghouse.com Challenges of doing Analytics Obtaining support from the TOP Establishing an Analytics culture across the organization Hiring and retaining right people Creating a single enterprise wide analytics initiative Models are difficult to build and maintain Using the right technology

9. www.reportinghouse.com Readiness assessment questionnaire Are we on a shaky foundation? Are we using analytics – really? Do our people even want a data democracy? Are we measuring the right things? When KPIs talk, who is supposed to act? Do we really have a handle on costs? Are we just watching the dials or moving them? Are we strategizing from the top or justifying from the bottom? Are we locking analytics in an ivory tower (strategic, analytical & operational)

10. www.reportinghouse.com Strengths of Maximo data Single source for work management data GL accounts and related expenditure Inventory data Material requests, Purchase requests and purchase orders Service request data Integrated asset management

11. www.reportinghouse.com Success factors Create a solid data foundation Look beyond the spreadsheet to predictive analytics and forecasting Identify and address cultural barriers to information sharing Use analytics to identify a limited set of metrics that really drive the business Implement processes and accountability to act on performance metrics

12. www.reportinghouse.com Success factors (cont’d) Look beyond gut forecasting to analytically derived forecasts Blend multiple forecasting methods to maximize predictive accuracy Adopt activity-based costing for a more accurate picture of profitability Don’t be satisfied with hindsight; use analytics to improve, learn and evolve

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14. What-If Analysis

15. www.reportinghouse.com Root Causes for Failures : Pareto Analysis

16. www.reportinghouse.com Reduce Shutdown and Downtime

17. www.reportinghouse.com Monitoring Cost and Number of Failures

18. www.reportinghouse.com Advanced Reliability Analysis

19. www.reportinghouse.com Interactive discussion What are your current successes and challenges of analyzing and effectively utilizing Maximo data?

20. www.reportinghouse.com Thank you Samir Vyas sam.vyas@reportinghouse.comsam.vyas@reportinghouse.com 919-345-1728 Pankaj Shetye pankaj.shetye@reportinghouse.compankaj.shetye@reportinghouse.com