Making better and faster decisions to drive efficiency and promote safety has long been a prime goal within the manufacturing sector.  In the past this has been achieved through analogue methods or collecting data, with good but error prone results. As manufacturing becomes more complex and the need for efficiency more pressing, many are turning to data. By becoming data-driven, manufacturers have the opportunity to harness accurate insights to inform decisions. If implemented and managed properly,  initiatives can come from all workers to optimise the business from the factory floor up. 

Becoming data-driven as an organisation requires more than just putting in new technology or digitising processes. To establish a data-driven culture and create a continuous cycle of value, it takes a holistic approach to systems, processes and organisation. When you try to change one aspect without changing the others, your data strategy will fail. Simply installing the appropriate systems will not get you much further. It’s the merging of systems with people and processes that creates a winning combination.

Data and analytics: putting in the right systems 

First, it is necessary to put all data from all different systems, applications, sensors and external parties together. Before you can analyse relevant insights, your so-called data estate must be connected. What systems should be in place and what challenges should be expected at each stage? 

  • Azure Data Lake

A data lake is a central repository where all of your data, both structured and unstructured, can be stored. It allows you to perform any kind of processing and analytics on any type of data, regardless of its size, shape, or speed. However, dumping data into the data lake would turn it into a data swamp that will prevent you from getting any insights.

  • Azure Synapse

We move on from the data lake to Azure Synapse, which is a comprehensive data analysis toolkit. It combines data integration, data warehousing and data analytics. Furthermore, it applies AI and machine learning models to your entire data set. Because the data lake is where all the data resides, there is an interdependency associated with it. A data dump is difficult to explore, whether you’re using Synapse or not.

  • Power BI

Assuming you can make sense of the data that is stored in your Data Lake and analysed through Azure Synapse, Power BI provides a powerful tool for visualising your insights. However, every employee at every level of the organisation should be able to understand these insights and dashboards. The extracted findings, on the other hand, mostly make sense to the person who collected them and converted them into reports and dashboards. It’s difficult for someone else to make decisions based on that.

A combination of the above three data and analytics platforms enables you to connect and analyse all of your data. If you overcome the accompanying challenges.

Combining your systems with processes 

Relying solely on systems will not get you there. It’s just the beginning. Because data will not provide you with the insights you expect unless you change your organisation. It’s the same as forming a team to discuss a product backlog and the direction of the reporting system without talking with the end users. 

The key is to make data and analytics relevant and useful to users. For instance, by allowing them to customise the reports and insights they require. Or locking the data set, to prevent data from being rewritten or modified. However, you should allow users to download and edit reports in order to create anything they want and experiment with the data. This guarantees BI self-service and data security without causing chaos or locking up data. In the end, data systems need to be flexible, secure and compliant.  

Holistic approach: Systems + Processes + Organisation  

When systems, processes and organisation are brought together, you create the best opportunity for a data-driven culture. The success of your data and analytics practice is limited if you only concentrate on the systems and processes. Equally as important is that you get buy-in from those who will use and enhance your dashboards and reports. To achieve this holistic approach, you need to talk about digital transformation.  

Working paperless is not the goal of digital transformation. Instead, it is to build a data-driven culture throughout the organisation. A data and analytics platform is not only for top managers to use, but for all employees. Data not only allows your employees to do their jobs better and work smarter, but it also helps in customer engagement, operations optimisation and product transformation. 

Modernise your data platform  

A modern data platform is the foundation of innovation and data-driven work. However, the right processes and empowered employees are also required. But how do you become a data-driven organisation? How can you teach employees to interpret data and recognise opportunities? What is the best way to convert data processes into business processes? All of this and more can be found in our whitepaper on data platform modernisation. 

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