Tag: data modelling


SpendEdge Webinar on 7th and 8th Feb – Is advanced analytics shaping the way procurement teams will look at data?

The procurement department is considered to be the backbone of any business – and even though for many years, the procurementyatheesh department functioned more or less the same way, the new wave of digital technology has led to a radical shift in that thinking. The rapid development of digital technologies has changed the business world altogether and is expected to grow at an unprecedented rate. So it is entirely possible that the procurement teams will be dealing with new sets of digital opportunities. The rapid evolution of data analytics capabilities has enabled companies to store and process a large volume of data to generate relevant business insights in real-time. Such insights provide valuable information to the procurement teams, which help them make smart decisions on spending, managing suppliers, and designing better strategies. In an era that is fiercely competitive, the use of data analytics in procurement functions becomes essential to gain a competitive advantage. In a few years, analytics in procurement will not only be a matter of gaining a competitive edge, but also a matter of survival.

What are the opportunities for advanced data analytics in the field of procurement?

sanyaFor a long time, businesses have been reliant on intelligence systems to process historical information and identify the current trends in the business. The capabilities of those systems were limited to the point where they could only help out with basic forecasting. However, data analytics has and will continue to have considerable implications in the field of procurement. Historical data can be used to generate meaningful insights and propel strategic business decisions. Big data and advanced data analytics can also enable automated P2P procurement, predictive strategic sourcing, and establish a proactive supplier relationship management strategy. The rapid evolution of the IoT will only exacerbate the vision of a fully automated future, moving procurement teams away from small, repetitive tasks to tasks that are more strategic in nature.

Conducted by SpendEdge’s procurement experts, this webinar on the 7th & 8th of Feb will cover the following:

  • What are predictive, prescriptive analytics, and advanced data analytics?
  • Explore how predictive analytics helps achieve efficiency in the procurement process lifecycle
  • Key non-procurement areas where advanced analytics could add significant value
  • Insights on successfully setting up a best-in-class advanced analytics strategy

emea audience

NA Audience


Top Procurement Trends in Air Quality Monitoring Market

Measurement of air quality is of vital importance to many businesses. In some sectors, it’s a means of attaining a healthy working atmosphere, whereas in others it can be of critical importance. For instance, a single speck of dust can ruin the functioning of an entire Request Free Samplechip. Organizations invest in top-notch air quality monitoring systems not only to improve the working conditions but also to comply with emission standards. They do so by employing various indoor and outdoor air quality monitoring (AQM) systems along with ozone monitoring and control systems.

Organizations and governments are demanding complex air quality monitoring systems as they have to adhere to stringent emissions regulations. Here are some of the procurement trends in the air quality monitoring market:

Demand for Real-Time Monitoring of Air Quality

Environment protection authorities are demanding real-time monitoring of air quality to monitor constant changes in the quality levels. This way, they can alert citizens to take protective measures such as wear masks in case the air quality exceeds the stipulated standards. For instance, air monitoring network in Queensland, Australia provides an hourly update on air quality and publishes the data immediately for corrective actions.

Use of Modeling Techniques for Air Quality Monitoring

More complex aspects of air quality monitoring require using mathematical simulation to derive a correlation between the source of emissions and its impact on ambient air quality. This way, authorities can use such models to anticipate the result of policy change aimed at reducing air pollution. AERMOD, CMAQ, C-LINE, and Downscaler models are some of the widely used modeling techniques by local authorities.

Cross Border Collaboration for Effective AQM 

It is essential for environmental agencies across different regions to collaborate on reducing emission levels. Collaborations across the geography amongst environmental agencies results in improvements in the air quality monitoring methodology. Such measures help them develop new measurement methods and achieve long-term sustainability results.

Read more about market development in air quality monitoring market along with supply market landscape, pricing, and procurement insights in SpendEdge’s upcoming procurement report on the air quality monitoring market.

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