Comparative assessment of S/4 HANA Product Compliance & ECC EHS – Dangerous Goods mgmt
For past many years we are used to the way…
For past many years we are used to the way…
A recent study pointed out that on an average 3.5 clinical encounters are recorded per patient per Year in United States and number of such encounters are equally same for employees when its comes to their annual medical examinations, vaccination programmes or even adhoc medical check-ups.
SAP Environmental Compliance 3.0 was historically used to manage the emission and environmental compliance (EC) requirements. However SAP recently released Environmental Management (EM) module as part of EHS management within ECC - Component Extensions and also as part of S4HANA releases. I happened to work very closely with Environmental Compliance 2.0 / 3.0 and have previously set up proof of concept system for Environmental Management as well.
Few days back many news agencies reported J&J recalled 33,000 bottles of its baby powder lot bearing the number 22318RB after health regulators found traces of asbestos. Its not uncommon that we hear such reports from different products which undergo recall to manage the risk and lawsuits. Usually such analysis of products when they are in supply chain is a critical requirement for many companies.
Recently Greenhouse Gas emissions account to major concern owning its beings a potential cause of Global warning. There are various sources / sinks for GHG emissions be it due to use of energy consumption or practices of agriculture methods or other anthropogenic sources.
As mentioned in the CCPS Process Safety Guide, an essential element of any improvement program is measure of existing and future performance. The proper analysis of such measures like Leading and Lagging metrices is critical for successful process safety management. Generally, a safety pyramid consists of mix of three types of metrices like Lagging metrices – which are retrospective set of measures, Leading metrices – which are forward looking metrices and finally Near-miss which are less severe incidents, which however are very good indicators for future likelihood.
Incident / Accident Management is requirement for many guidelines and regulations and needed to be properly managed within an organization. If an incident is not properly managed it results in loss of information, chances for incident avoidance in future and monetary challenges. Deep Learning Techniques like Tensorflow / Keras along with OpenCV and other libraries can be used to automatically manage incidents / accidents within an organization.
A strategic paper mention's that around 60% of human tasks will be automated by year 2025. The level of automation has become very sophisticated due to the availability of different technologies. The intelligent enterprise which evolved from mainframe era, comprises of business suite, digital platform and intelligent technologies.
Moving away from paper-based tracking system to automated way of managing it via ERP software is one of the major achievement for many organizations. Mere using the technology to capture the incident information is a normal business as usual practice, effectively harnessing the technology to support risk management is the greatest opportunity for most organizations. Risk Management not only enable the performance but also protect the business. It is found that majority of drivers for operational risk management are technological in nature like Industry 4.0 principles, competitive marketspace and cost-effective data automation.
EHS falls under the digital manufacturing suite in the current solution plan. Started with product safety, chemical safety and functionality added over the years. It started off in the year 1995 with the Foundation – chemical safety which over the years moved to health and safety module covering Industrial hygiene and safety, hazardous substance management and occupational health.