Advanced Analytics & AI
Unlock The Power of Insight
Successfully implementing a modern data estate has quickly shifted away from the monolithic data warehouse designs of the recent past. Increased focus on data governance, accuracy, and relevance are helping companies and their employees unlock new potential.
Aligning to the right goals before development begins reduces time to value and supports agile development practices with iterative delivery of value. Our DEEPER approach shows how companies can enable their workforce with advanced analytics and the insights to unlock value. Innovation in application and organizational development have driven highly decentralized information domains.
This has enabled technologies to radically transform single loop learning and problem solving (eg. if inventory is low order more). Many organizations still have a ways to go to fully extract value from these innovations. However, additional and often greater value can be extracted through innovation in double loop learning. These solutions subject organizations to changes around people and process, and require robust feedback systems to deploy, test, assess, and refine theories.
- Data starts decentralized, aggregating core business entities and putting in place an organizational glossary begins to uncover the information locked in subsystem data.
- Establish processes to collect data, owners to ensure adherence, and data stewards to ensure quality allows the organization to begin building a trusted repository of information. Combined with a organizational objectives, metrics, and goals a descriptive analytics solution serves as a foundation.
Analyzing data requires a mix of generalized business knowledge, deep domain understanding, and accessibility of data.
- Designing visualizations, dashboards, and drill throughs based on target organizational roles helps pair data and actors to align on a set of actions to improve outcomes.
- Extracting key correlations, influencing metrics, and trends is the final step of analysis. These extractions serve as the foundation for process improvement projects to come and serve as the core measurements of there success as actions are taken to remediate.
- Refactoring learnings from your analysis into action can be the hardest step. Armed with data, a clear value proposition, and the ability to measure it’s efficacy decreases resistance and provides transparency around the initiative.
Reference Data Architecture
Many companies focus on how many data sources they have when building or moving their data estate to the cloud. This idea, extrapolated from the belief that more is better and that employees will be able to successfully navigate and gain insight in and ad-hoc or self-service fashion can be a costly mistake.
CRMs, ERPs, and the plethora of custom or COTS line of business applications can have thousands of tables and hundreds of thousands of data points. Only a small fraction of which hold insight for the core business. We help you cut through the noise, quickly identifying the metrics that will drive your business and put them front and center to align your people and organization to the strategy at hand.