Prediction by Zahara merges and collates previously disconnected information into a powerful knowledge base that is accessible anytime from anywhere in the world. Vital information in the Prediction Suite database affords an organization the ability to support extensive analysis, clear understanding of performance issues and advanced collaborative systems for planning, executing and learning.
– All of this is achieved from the data that is already being collected. –
Prediction by Zahara allows a leadership team to benchmark performance, identify improvement opportunities and ultimately accelerate the learning curve. Achieved through a collaborative approach or individually. The earlier the engagement, the greater the opportunity for early learning.
Dedicated, instantaneous data analysis ensures the operational leadership team can confidently focus their undivided attention on managing operations and logistics, with the assurance that they have the resources in place to track performance, close out lessons learned and drive the optimization process.
Pioneering a Vision
The best ideas are inspired by fresh approaches to solving customers’ needs. That’s why we bring the entire operation together, an end-to-end solution, to overcome the challenges currently experienced to spark innovative and meaningful results.
Using Data and Ultimately Trends to Deliver Meaningful Results
We put the Cloud, IoT, AI and Machine Learning to work for you in powerful ways. Complete automation allows analysis without the need to sift through large data sets. Given data is, with the exclusion of people, the single most valuable asset to an organization. It is the parametric outputs in which all decisions are made. With it an organization has the ability to ensure they initially understand when a problem is occurring and then ensure they do not the repeat the mistake. Prediction by Zahara allows the user the ability to be proactive with their decisions without having to wait for end of well reports or lessons learnt. Effectively incorporating lessons learnt the following day not the following well.