Monday, June 8, 2009

The LyondellBasell Matagorda site will share a new approach to driving continuous improvement and performing required VPP site inspections with new vigor and efficiency through their Planned Inspection Team and procedure. Learn how to rejuvenate your site inspections, engage the entire site, and increase overall effectiveness of your VPP site inspection process.

The Safe Acts Index (SAI) is a behavior based auditing system used as a leading indicator to measure at risk behavior of employees working in a facility. SAI is based on a the number of employees performing work while accepting some tolerance of risk. Unsafe acts and or at risk behaviors identified during the audits are weighted by severity and potential for injury. These factors impact the calculated SAI score. The severity categories are Low, Medium, and High potential for injury. As at risk behaviors are identified, immediate intervention and corrective actions are taken to correct the behaviors. To drive consistency in the risk weighting decision, a standard list of unsafe acts is used and the audits are conducted by a core group of trained safety personnel selected by the site.

A weekly SAI report is communicated to all site employees which, in addition to the SAI score, includes a description of items identified and the weighted risk factor for the items as well as other information that identifies additional focus areas needed by work groups across the site.

The intent is that this information be used in a proactive manner in safety meetings to help promote increased awareness for areas, identify trends in the work force and provide the site with a weekly report card on risk tolerant behavior.

With many new fabric and garment manufacturers on the market, proper labeling of flame resistant & retardant clothing (FRC) takes on an increasingly important role. And as companies complete their arc hazard analysis, layering of FRC has again become a topic of debate. This session will explore the standards that address labeling (including ASTM F2302-08 & ANSI 107-2004), will teach you what to look for in your FRC to ensure your workers are protected, and will discuss the consequences of outfitting your workers in improperly labeled clothing. This session will also review the layering requirements in the NESC, OSHA 1910.269 and NFPA 70E standards, as well as answering such questions as "how do I accurately calculate the protection level of a layered system", "how do I know when my employees are adequately protected", and "what is the best practice for determining an arc rating of a layered system when test data is not available".

What does one of the most in-depth management studies ever undertaken tell us about the central characteristics of the most successful managers? It tells us that providing employees with frequent and effective recognition is vital. Based on over 200,000 interviews conducted by The Jackson Organization, this session will explore the work of leadership experts Adrian Gostick and Chester Elton who have illustrated the effectiveness of constructive praise and meaningful rewards as the means to powerfully motivate employees to excel. These findings, which Gostick and Elton have termed the "Carrot Principle", demonstrate that recognition done correctly, and when combined with four additional core traits of effective leadership, produce an enhanced level of commitment and an increased employee desire for achievement. This session will explore these findings, explain the relationship between recognition and improved business results, demonstrate how effective recognition translates into improved employee attitudes toward work, and illustrate how the best managers use recognition to engage their employees, retain talent and accelerate work performance.

Have you found the leading indicators for which continued execution TRULY does result in fewer injuries, less spills, and generally better QHSE performance? If so, can you prove it? If not, is it something you wish to do? This session will dive into the increasingly hot topic of Leading Indicators, and how combining a large global data set with some fundamental statistical methods can result in both finding those factors which TRULY affect performance outcomes and the mathematical support to prove it.