CASE STUDY
And, of course, this is real life so we weren’ t operating in a vacuum. As important as the migration was, it wasn’ t our team’ s only focus. Business as usual continued so there were constant demands and modifications to business operations that added complexity to the project.
Bringing Syniti in when we did helped us to address our data quality from the outset, rather than later down the line when extra pressures would have been mounting. By prioritising the data – making sure that we only migrated accurate, up-to-date data we needed and removing unnecessary duplicates – we were able to move 100 % of our master data to SAP S / 4HANA, meeting that ambitious deadline.
We chose to work with Syniti, and the difference was tangible. The team used a previously installed version of Syniti Knowledge Platform to re-align the set-up and design and deliver a 90 % improvement in our migrated master data accuracy.
If you asked me what lesson I learned after the final, successful go-live, it would be that you can never focus on data quality too early when it comes to a complex migration like this.
Can you elaborate on how the 90 % improvement in master data accuracy has impacted Bridgestone’ s operations?
The Syniti team also helped us to improve our data governance strategy and processes, so that going forward, our data remains in good shape.
Bridgestone’ s Digital Transformation spanned 26 European countries. How did you manage to ensure consistent business process consolidation across such a vast region?
Twenty-six countries is a big undertaking! As you can imagine, over time different data management practices had developed and we were dealing with inconsistencies and siloes that could have caused us serious challenges closer to go-live.
As it was, Syniti’ s Data First approach served us well. It meant we spent time tackling data quality before we even began to consider moving it. The Syniti team also helped us to develop our data management governance. They introduced standard rules and processes for our teams to follow so that we didn’ t spend months addressing our data quality, only to discover it had reverted to its original state before we had a chance to migrate.
You mentioned that previous Big Bang go-live attempts faced challenges. How did the approach with Syniti differ, and what lessons were learned from the earlier experiences?
Migrations like this often involve dynamic business operations. Data that is constantly changing, from operations like finance and accounting and supply chain management. Our migration was no different.
From our past attempts at go-lives, we knew we needed a flexible approach that would allow for ongoing modifications throughout the migration process. And we also realised that we needed support to develop that approach.
The obvious and most measurable impact is that we successfully migrated to SAP S / 4HANA. Business continued on the day after the migration which is every CIO’ s priority for this kind of project.
However, we didn’ t migrate to S / 4HANA simply because it was there. When you undertake such a complex project, there have to be long-term business benefits too. These benefits can only be realised if the platform is delivering on its promise, and it can only deliver if it’ s using high quality data.
That 90 % improvement in data quality has set us up for the future. We have better visibility and transparency across our operations so we can be more efficient. We have automated systems that have reduced the need for manual data validation. And we have trustworthy data for improved decision-making.
And it means we are ready for the future.
How do you see Bridgestone leveraging its SAP S / 4HANA Cloud platform to drive further innovation and automation in the tyre and mobility sectors?
Bridgestone has committed to become a sustainable solutions company, providing both social and customer value through our products and services. This is our driver when it comes to innovation and automation, and one of the reasons we chose to migrate to SAP S / 4HANA when we did, was because of the opportunities it presented.
It allows us to focus on sustainable products and mobility solutions. And its advanced analytics capabilities mean that we are able to drive automation in key areas like predictive maintenance and customer service, which enhances our operational efficiency and customer satisfaction. p
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