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More than ever before , consumers want to be able to easily access a variety of details about the products they buy . Data such as ingredients , level of sustainability and the where it was sourced is becoming more important to enhance the product experience . This transparency enables consumers to be informed about the eco-responsibility of their brand . Details around a product are no longer just marketing claims ; they are statements that companies must be able to back up with data . Gaining visibility into the performance of manufacturing across the supply chain is a big challenge and means companies are in a constant battle to collect information and then make it actionable .

Complexity in leveraging growing amounts of data

Over the past five years , the majority of consumer product and retail companies have focused on collecting enormous amounts of data . When manual analytics are run on data stored inside a common database , context is easily lost . Companies can present insights into individual silos of information but cannot gather intelligence across common processes or from information stored in various global manufacturing facilities . In the absence of data contextualization , it is difficult to run analysis and gain insights on innovative practices . More specifically , when considering the current processes for collecting and connecting data that showcase process reliability and effectiveness on the shop floor , companies often struggle to find effective ways to capture , analyze and present information in a userfriendly way .

Many companies in the consumer products and retail ( CP & R ) industry have acquired automation , manufacturing execution and enterprise resource planning ( ERP ) systems during the past decades . These systems have become part

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