Leveraging Maximo data to increase Asset effectiveness ROI

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

Data Explosion in Maximo www. reportinghouse. com

Business Analytics 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 www. reportinghouse. com

Growth of Analytics 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 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 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) 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 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 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 www. reportinghouse. com

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What-If Analysis www. reportinghouse. com

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

Reduce Shutdown and Downtime www. reportinghouse. com

Monitoring Cost and Number of Failures www. reportinghouse. com

Advanced Reliability Analysis www. reportinghouse. com

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

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