The data landscape is ever evolving, and procurement is bound to feel the impacts of these changes. These four trends in data analytics are expected to continue through the coming year and will have serious implications for Procurement.

Chief Data Officers will be in high demand
Data is becoming an essential part of modern business. In the growing landscape of data technologies, firms need an expert to build out their data & analytics programs, enter: Chief Data Officers (CDOs). The CDOs primary responsibility is to design in-house analytical and technical capacities that can seamlessly process, manage, and analyze data to support and drive business objectives. Such an individual must not only have comprehensive knowledge of data technologies and business strategy, but also understand how to bridge the gap between the two. This gap is most often the result of lacked knowledge and poor communication and is a common roadblock for many analytics organizations.

CDOs will have a significant role in enhancing the performance of procurement organizations. Given that procurement is an essential part of business objectives, part of the CDOs job will be to ensure that procurement teams have the analytical capacity they need to achieve their benchmarks and stay competitive in the marketplace. With a CDO in place, you can expect procurement analytics to get the management and resources it needs to flourish.

Decentralized Data Systems are on the rise:
Some of the hottest new analytics technologies today involve the decentralization of data processes. Decentralization aims to address the storage, speed and processing limitations associated with massive centralized cloud-based data systems by distributing these processes across nodes (sub-systems). Edge Computing is a decentralized technology that distributes the processing of data across a set of interconnected devices in a network that can be used to collect, store, and present data back to an end user. In other words, data is maintained at the "edges" of the system.

Recently developed models of decentralized, or federated data governance are better suited for some organizations. Instead of using strict company-wide methods to ensure data quality, decentralized governance allows different models and methods to be utilized across different business strata. It is likely that most organizations will begin to perfect hybrid models that incorporate both top down and local data governance practices.

New decentralized technologies and concepts will integrate in to the various data systems used by procurement. Edge computing, for example, will increase efficiency, and lower costs involved with logistics by distributing collection, analysis, and reporting to end-user devices throughout the logistics network.
Internet of Things will harness streaming data
The Internet of Things is composed of billions of internet connected devices that share information and control different systems. One exciting new advancement harnesses IoT to enable real-time processing of data. In other words, data is analyzed as it is collected. This breakthrough is particularly impactful in that it allows predictive analytics and machine learning models to produce insights, and update themselves in real time. By eliminating the time consumed sending data through a pipeline, quantitative information can yield insights instantaneously. Even better, machine learning models can train and improve themselves based on up to date data, ensuring that the models are as well.

Expanding on the application described in the previous section, streaming data will significantly improve a procurement organizations logistics management. Managers will always be sure to have the most up to date insights about the status of their freight, and distribution centers, while predictive models will always be tailored to the most current information. 

Dark Data will come in to the light
IoT data collection is ubiquitous in the modern technological landscape. Companies are continuously harvesting data from the countless nodes in their technology systems. So much data is produced in fact, that there exist vast pools of unused, unstructured data; this is referred to as Dark Data (data that in its current state provides no information to users). As data storage and migration technologies continue to advance, it gets easier and easier for this data to be migrated to the cloud, and harnessed using cloud-based predictive analytics. Every data-empowered organization will benefit as access to dark data improves, and procurement is no exception.
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Ari Markowitz

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