TECHNOLOGY
to tweak operations and workflows where changes will have a positive impact , without spending money on solutions when they are not necessarily needed .”
Successfully adopting a data first strategy both agree on what a data strategy consists of Beck and Zimmermann both agree that a successful data-first strategy encompasses both culture and technology .
“ In my opinion , the most important thing is the right mindset . Trust your data , work on your data quality , establish data governance , and start collecting data . A successful datafirst strategy is not brought to life overnight , it is a journey . Start with small overseeable pilots to build on and gain trust in your data across your organisation . As these first successes continue , convince people of the benefits of using their adequate data ,” says Beck .
Expanding on this , Zimmermann adds ; “ manufacturers that want to build a data culture need to address data governance and data literacy in order to enable stakeholders to access trusted data assets from across the whole business and answer new questions without over-reliance on core IT .
“ To deliver an agile data foundation , manufacturers should look at creating a single source of truth that pulls together data from across the entire business . They can leverage low-code or no-code , cloud-based , SaaS data management and analytics platforms to enable more parts of the business to selfserve data and insights .
Manufacturers should then look for ways to bring those insights into key business apps so that front-line workers can use them as a seamless part of their workflow .”
Enter , predictive analytics … “ Per definition , predictive analytics tells you what is going to happen next based on
“ 87 % of CXOs say that being an intelligent enterprise is their top priority , the reality is that only 30 % of frontline employees actions are driven by data analysis ”
FRANCOIS ZIMMERMANN EMEA FIELD CTO , TABLEAU SOFTWARE
trained models and historical data – so by referencing a past experience ,” says Beck , which is why he defines it as “ the most valuable use case .”
Predictive analytics assesses workflows and finds inefficiencies to predict future events i . e . How might a supply chain hold up under X or Y conditions ? What points of weakness might create issues under specific sets of circumstances ?
“ Using historical and real-time data , predictive analytics can bring to light possible future outcomes and identify potential issues that manufacturers can then preemptively mitigate . This enables manufacturers to make data-driven decisions about their business with full endto-end visibility ,” adds Zimmermann .
How can predictive analytics help manufacturers to improve their operation ? By harnessing predictive analytics , manufacturers can improve their operations
122 December 2021