When I first joined Vincit, the company lived up to the old phrase “the cobbler’s children have no shoes.” Even though we had successfully helped many companies undergo a data-driven transformation, data in Vincit was still siloed and based on manual reporting processes. This meant we lacked a single source of truth about our customers and couldn’t learn from data quickly.
Becoming a data-driven business
1. Increase reporting automation from 20% to 80% and turn controllers into advisors for business
2. Increase learning cycles with more timely reporting
3. Embrace the culture of business accountability
We followed a three-step process to successfully meet our goals. Here’s how:
Step 1: Establish a strong data foundation
Creating a data-driven company requires a solid data foundation. This ensures that information from various source systems is harmonized, consistent, and accessible. By incorporating best practices in data governance, security, and compliance, companies can trust their data and rapidly scale operations as new needs arise.
In our transformation, we established a future-proof infrastructure that underpins all analytics and AI initiatives – fostering data-driven innovation and collaboration. This helps enable data-driven leadership.
Step 2: Use data analytics for decision-making
To make smarter and faster decisions, you need to turn data into clear, contextual insights that empower every level of the organization. By designing intuitive dashboards and deploying advanced analytics, teams can quickly identify trends, measure performance against key metrics, pivot in real-time, and create data-driven business strategies.
During our data-driven transformation, we focused on human-centric solutions to ensure that information is tailored to specific roles and delivered seamlessly. This clarity fosters rapid, evidence-based decision-making that translates into tangible business results.
Step 3: Boost AI and automation in business
To increase efficiency and get more accurate insights, automation and AI are key. They offer the fastest route to scaling efficiency and uncovering opportunities hidden within data. By automating repetitive tasks, teams can reclaim valuable time that can be used for innovation and problem-solving instead. Meanwhile, advanced machine learning models amplify your ability to predict customer behavior, optimize pricing strategies, or detect operational anomalies in real time.
In our case, we focused on both the technical backbone and user experience. The result is a self-improving ecosystem where AI-driven insights continuously guide smarter, more proactive decisions.
The benefits of a digital transformation with data
- A single source of truth – a solid foundation that integrates data from various source systems into a platform provides harmonized, consistent, and accessible data.
- From data to insights – dashboards for different roles and functions allow people in the company to use data for decision-making. Using AI for advanced analytics allows for predictions and anomaly detection. Controllers can move from only looking at the past to looking to the future, becoming advisors. Data also enables supply chain management, allowing businesses to become more responsive and efficient.
- Accelerated learning – a data platform and automation speed up reporting cycles. For example, at Vincit, we’ve improved our reporting frequency from 12 times per year to 52 times per year – and continue to aim for 220 times per year. This gives a much better capability to lead business proactively.
Kimmo Kärkkäinen,
Chief Financial Officer, Vincit
