“Truth is ever to be found in the simplicity, and not in the multiplicity and confusion of things.”
― Isaac Newton
Traditional BI systems while trying to be comprehensive are typically too cluttered with hundreds of metrics & drill-downs that are static. Users hardly get time to drill down and glance through each metric at every possible level. Also, the same BI system is subject to the interpretation of different users and hence not standardized to focus on the right metrics at the right level of granularity. It not only presents the opportunity of missing out on key business development at a given level of hierarchy but also poses a challenge of individual bias.
In the digital age with an abundance of data, manual tracking of metrics with multiple business hierarchies is not humanly possible and hence it demands a smart BI system that can alert users if there is any interesting pattern arising in any metrics. Also, alerting might not be enough but it should also be able to point out reasons of the pattern and guide users in understanding the pattern better. According to a Gartner research, BI system should also be able to estimate the potential impact of pattern/anomaly. The integration of a smart BI system with chatbot or voice assistants like Alexa might help users who are not familiar with the flow of BI tools to generate their own report without being dependent on assistants.
What’s Our Take?
BRIDGEi2i’s AI-powered Watchtower™ leverages various proprietary self-learning algorithms to map causal relations and correlation between metrics. Watchtower™ uses ML algorithms to tracks thousands of metrics in real-time and identifies if there is a new pattern arising in data. It alerts users if any new patterns are emerging. The Watchtower™ generates a simple text narrative to explain alerts. Associated root causes/factors, as well as potential business impacts of alerts, are also highlighted and plotted to help users understand alerts better and act on it. It also makes information consistent across organizations without being dependent on user bias. Watchtower™ helps business users spend less time going through reports and still not missing out on any significant patterns and hence allows them to focus on more important tasks at their hands.
We helped a global networking augment their sales and channel strategy.
How Did We Enable This?
The Watchtower™ uses proprietary ML algorithms to learn patterns from thousands of metrics dynamically and identify if there is any abnormal/anomalous pattern arising in data. The causal model is used to understand causal relations between metrics. Causal relations help us discover associated root causes for anomalies which might not be possible in traditional dashboards where bi-variate/tri-variate charts are generally static. Causal relations, business hierarchies and output of pattern/anomaly detection modules are stored in the graph database. Graph database is being used to query large sets of relations and business hierarchies to make search faster and scalable. User feedback provided for alerts is being captured and used to finetune algorithms. The Watchtower™ can also be configured to navigate through voice command or chat. BRIDGEi2i’s Watchtower™ can be applied to any functional and business areas with customization. The Sales & Pricing Watchtower™ helped a global manufacturer of personal care products to reduce the share gap of their lip balm against the market leader by better price monitoring while reducing compliance effort by over 30%. You can read the details here.