From data to value
We help you turn your data into true competitive advantage. To avoid poor decisions being made that will hurt the business, we work together with you to ensure the metrics you use are relevant and meaningful.
We analyse the data and convert it into accurate, actionable information that can support fact-driven decision-making to improve your operational effectiveness and efficiency, and we test the results of your customer-facing digital initiatives to ensure maximum impact.
We take either a process-centric approach, a data-centric approach or a combination of both, to suit the situation.
Our highly skilled team can help you build an advanced analytics organisation, embedding the capabilities you need to execute your analytics strategies consistently while also addressing the change management issues that naturally arise.
Robotic Process Automation (RPA)
Although companies have automated many of their business processes, much of the routine, repetitive manual work still remains. For example, employees still need to enter data manually and switch between systems, applications and screens to allow the critical business processes to function. Such activities in themselves do not add value; furthermore, they take time and are inherently risk prone and expensive.
RPA copies an employee’s tasks and executes them fast and without mistakes – 24/7. This allows employees to add value by concentrating on tasks that require their attention and expertise. The time freed-up facilitates the transition from reactive to proactive operational processes.
We consider Maintenance to be a value creator rather than a cost generator. Therefore, we focus on the most critical assets from a combined risk and customer’s point of view: overall reliability and quality of output, and technical and technological integrity of the equipment.
Maintenance 4.0 is a next step on the ladder of Maintenance maturity, creating increased reliability, better product quality and a further drop in cost. The implementation of Maintenance 4.0 starts with ensuring the basic conditions are in place: high-level preventive maintenance and good quality data on the historic behaviour of the selected equipment, product quality and process settings.
Our data scientists team up with your reliability engineers and process technologists and challenge each other to develop a first algorithm to carefully deploy. Additional data requirements and sensors are then explored. Through a tightly guided process the most relevant data points, sensors and other requirements are identified. The algorithm is improved and more business value is created.