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Part 4/5: Data-driven efficiency: What does it mean and how to achieve it?

Before reading further, I ask you to stop here and think: what do the title’s three words mean to you? How do you interpret “Data-driven efficiency”? Is it part of your day-to-day work? Is it something that requires or enables actions and decisions in your work? What are the enablers and requirements for you to achieve data-driven efficiency? If you ask the same questions from your colleagues, can you expect similar answers to yours?

We can start answering these questions by checking the English dictionary for their definitions;

This gives us quite a clear definition: “Use data to define actions which provide the best outcome.” 

Data alone is not enough

Data requires a variety of actions throughout its lifecycle. It has to be created, collected, verified, owned, maintained, cleansed, represented and integrated between systems. So, one may say that handling data takes a lot of effort and gives you pieces of information that do not improve your efficiency on their own.

In many organisations, efficiency - the best outcome - is a blurry target, as there are a lot of different views of what it means. If you happen to have the same situation with your data and have your facts and numbers inaccurate or not available, the decision-making to define actions that improve efficiency gets very difficult. 

Business targets are an essential requirement for reaching data-driven efficiency, while digitalisation and emerging technologies are its enablers. The ability to collect, share and process data increases day by day and these technologies provide more and more real-time data from all levels of your operations and supply chain. Therefore, it is a common challenge to have plenty of different technologies providing huge amounts of data but not know exactly how to make the best out of it.

My approach

At Midagon, we help our clients to proceed in their pursuit of improved operations. To succeed in data-driven efficiency, data and technology need to be aligned and seen as enablers for the targeted business benefits. 

Our maturity assessment identifies organisational capabilities and development needs, providing a  foundation for successful decision-making and target-setting before development initiatives are launched. 

For me, data-driven efficiency means continuous actions to implement strategic decisions to improve the business from carefully selected perspectives so that data and technology is used optimally. Examples of the results what I have seen achieved with data-driven efficiency include:

Read more: Improving industrial efficiency with balanced mechanical efficiency and personnel satisfaction”

With the help of our methods and expertise, together we can discover and achieve the production transformation opportunities that data-driven efficiency offers in your business landscape. We can start the discussions for example from these questions aiming to define your current state;

I’m happy to discuss more in detail with you of your needs in this area! This blog resumes our industrial production transformation blog series - read also: Manufacturing Efficiency- Point of View”. 

About the author:

Antti Ruohola has 15+ years of experience in supply chain roles: leading factory operations, Material Management and Purchasing. His expertise includes:

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