Kanu Equipment uncovered millions in un-invoiced revenue and used data-driven stock management to double revenue without increasing its stock holding.
In the heart of Africa, where mining, construction, and agriculture drive progress and growth is Kanu Equipment, a supplier of world-class earthmoving, mining, construction, agriculture, and forestry equipment. With a footprint in 15 African countries, Kanu Equipment is one of the largest distributors of premium heavy equipment on the continent.
Heavy equipment lifecycles are vastly different to those of other vehicles. Nuances in usage can result in changes in the lifespan of parts and servicing requirements. For Kanu Equipment, applying a one-size-fits-all approach resulted in significant inefficiencies, with millions sitting tied up in parts stock that couldn’t be moved.
Kanu Equipment’s leadership recognised the need to leverage the data built up over a decade of equipment sales and servicing to better understand the requirements of its customers. For this, it turned to its Chief Information Officer (CIO), Anja Goosen. Coming from a finance background and finding herself custodian, not only of the organisation’s data, but of its entire technology infrastructure, Anja found herself in somewhat unfamiliar territory. To be successful, she needed a partner she could rely on for pragmatic, transparent advice. For this, she turned to the organisation’s long-standing technology partner, Cyberlogic, and its business intelligence team, DataGeek.
Where there’s efficiency, there’s profit.
In analysing stock levels, Anja found parts were being ordered based on manufacturer recommendations, but, in many cases, those parts weren’t yet needed by customers. And so, the parts sat on shelves, gathering dust, which negatively impacted capital and cashflow. Conversely, the parts that were needed weren’t being ordered in advance, resulting in long service turnaround times.
Anja developed a model that highlighted trends related to parts. This enabled stock controllers with no technical background in data to place advanced orders for the parts most likely to be needed. The model ensured the business had the right parts available when it needed them. This reduced service turnaround times, unlocked millions in additional revenue, and reduced stock holding requirements. “Just using data correctly allowed us to double revenue, without increasing our stockholding.” Anja shared.
A need for scalability and flexibility
Throughout her career, Anja had been interested in data and how it could be used to enable better decisioning, greater business agility, and improved profitability. Anja had made great progress in her quest to “embed data in every decision”, but Kanu Equipment’s rapid growth had resulted in a data set that was too big to process within the current data architecture. The analytical models she’d built were failing because data replication was simply too onerous. “It was just getting too big, the business is becoming more sophisticated, but we’re working on a system and table structure that’s 10 years old.”
The aging data architecture desperately needed an overhaul to enable the scalability required by the business. Ian van Niekerk, Cyberlogic DataGeek’s Head Data Architect recommended a robust data warehousing solution to enable a scalable data solution that could grow with the business. Choosing to use an external provider also gave Anja flexibility in the skills mix. “What we needed was to pay the same as one salary but have multiple specialists. This way, we have access to different skills and the skills mix can change as our needs change.” The decision to outsource enabled scalability and flexibility in their data team, ensuring the team could grow or shift focus as the needs of the business changed.
The sweet spot
Kanu Equipment’s data landscape has evolved and grown along with the business. Data is now firmly entrenched in every major business decision. Whether it’s highly effective stock management or understanding the root causes of customer queries, data is at the core. And while Anja is at the heart of that transformation, she credits Kanu Equipment CEO, Stephen Smithyman, as being the reason it has been so thoroughly embraced. “I think what has made this really work was CEO buy-in.”
When asked how she went about getting that buy-in, Anja insists the data did the bulk of the work. She was able to quickly prove value and demonstrate the power of the data by finding millions in un-invoiced revenue locked in inefficient processes. The second key component was making it simple enough that anyone in the business could use it. “The trick is to make something that's very complex, simple enough for the user – a stock or a machine specialist – to understand and use it correctly. That’s the sweet spot.”
What’s next?
For Anja and Kanu Equipment, the next step is to shift from retrospective analytics into true predictive analytics. “We’ve become really good at making decisions based on historic information, but we need to start building predictive analytics – that is the vision.” With a scalable data warehouse and a powerful data visualisation engine in place, it’s possible to analyse specific ‘point-in-time’ data and build a view of trends. This can be used to predict future sales opportunities and likely servicing and stock requirements, driving increased revenue and greater profit margins.
Although Kanu Equipment, by Anja’s own admission, is still in the relatively early stages of its data journey, Anja and the Cyberlogic DataGeek team have made great strides towards achieving the vision of predictive analytics.
To find out more about how Cyberlogic can help your business harness the power of data to unlock exponential value, get in touch.