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What sets successful companies apart from struggling ones? Fast and smart decision-making. To achieve that, you need to unlock the potential of all available data to base those decisions on. In short: it’s necessary to become a data-driven company. Easier said than done, right? Explore the road ahead by learning more about this global manufacturing company’s transformation into a data-driven organization.
Turning data silos into a single source of truth
Nowadays a lack of data sources is not a problem. For a global manufacturing company with thousands of employees in over 100 production sites, enormous volumes of qualitative and quantitative data are collected. ERP data, manufacturing data, sales and finance applications, CRM and HRM systems… They all add up to over 50 data sources.
Acquisitions form a typical challenge for companies of this size, since most of this data is isolated in data silos. This means that it takes a lot of manual labor to govern and analyze it. Since each country – and even each site, in some cases – has its own data sources, they are reporting on this information each in their own way.
For example, there are more than 6 different reporting tools in use, from familiar Microsoft Excel to more specialized tools and legacy platforms like Hyperion and Cognos. Imagine the difficulty of reaching conclusions – and consequently, making decisions – for the entire group based on varied reports from all sites and domains. On average, it takes 8 to 10 days to consolidate sales and finance reports, meaning that executives don’t get the insights they need to make agile decisions.
Consequently, it takes 8 to 10 days to consolidate reports, which strongly impacts agile decision-making
The ultimate goal?
To create a central IT landscape at the company’s headquarters. With all data unified and collected in one data platform, it’s possible to make quick and informed decisions on a group level. But even more, a data platform is necessary for a future-proof approach to manufacturing, and to pave the way for advanced analytics and Industry 4.0.
Creating a cloud-based data platform
Our client identified three steps to achieving this data-driven approach:
Step 1: Define an executive data strategy
To achieve the benefits of a data-driven approach, it is essential to define a data strategy to ensure the entire executive leadership understands and supports the approach. This strategy consists of two pillars:
Data governance
What data is available?
How is it collected and stored?
What is its quality and security?
More on data governance and how to make data manageable.
Data analytics
How is this data applied to improve business decisions, unlock insights and develop new applications and technologies?
More on business intelligence and how to make right decisions based on data.
Step 2: Implement a cloud-based data platform
The data platform must support and answer to these requirements:
- Scalability: it must be able to grow with the company’s data needs;
- Global accessibility for all users;
- PaaS and SaaS first to focus on new use cases implementation, enabling innovation easily;
- Self-service BI, for personalized reporting with the right governance and adoption;
- Data as a service to onboard new data sources quickly and secure.
Step 3: Create an agile and centralized data & AI competence center
The technology is just one part of the equation. A truly data-driven company adapts its processes to data insights and creates new innovations and improvements from within. How should different countries be onboarded? What’s the best way to change the mindsets of people who are used to ‘the old way’ of working? Part of the solution is creating a competence center: a dedicated data team within the company that sparks new ideas and drives future technologies or improvements.
This competence center has numerous tasks:
- It serves as an agile data development factory;
- It centralizes data and analytics-related knowledge in the company;
- It supports and serves the data community;
- It ensure adoption.
Future-proof processes
We’ve invested in the data platform, but what are the returns?
The benefits of a cloud-based data platform are twofold. Not only can the group make quicker and more informed decisions, but the platform’s agile, scalable infrastructure and service-based architecture offer unbeatable future-proofness. As a result, it’s possible to implement and upgrade whenever needed.
Consolidated reporting
Instead of 8 to 10 days, reports now take just one day to reach the executive level. This means quicker strategic decisions.
Centralized insights
Whether the data is coming from HR, finance, health and safety or other domains, all data streams have been migrated to one data platform. With data as a service, new data sources can be easily onboarded.
Self-service BI
More than 1,000 users now have access to a self-service BI tool. They don’t need to spend their time creating countless Excel files. The insights are right there, enabling business employees to focus on the analysis and actions to take.
Global accessibility
The modern data platform is now globally available, IoT-ready, futureproof and scalable.
A data platform and beyond – future possibilities
Although the immediate challenges have been tackled, a data-driven organization shouldn’t rest on its laurels. In an ever-evolving landscape, a good data platform also makes an enterprise futureproof and ready to rapidly embrace new developments.
The manufacturing company actively seeks out new technologies that will keep the group on track in the future. When introducing use cases like predictive maintenance or quality assurance, new types of data needs to be onboared for example IoT, sensors, PLCs and more. Thes new types data streams deed to be easily analysed and integrated into the existing data platform.
Our team has guided a number of companies on the road to becoming data-driven enterprises. The manufacturing company applied the Cegeka reference architecture as a blueprint.
Kristel Demotte
Global VP Data Solutions