Are you data-flooded, data-driven, data informed? Are you outcome oriented, insight driven or hindsight driven?
Are you a firm where executives claim – “Data is our competitive advantage.” Or sprout analogies like, “data is the new oil”.
The challenge I found in most companies is not dearth of vision… everyone has a strategy and a 100,000 ft general view of the importance or value of data. Every executive can parrot the importance of data and being data-driven.
The challenge is the next step….so, how are you going to create new data products? How are you going to execute a data driven strategy? How are you going to monetize data assets? What are the right business use cases to focus on? How to map the use case to underlying models and data requirements? What platform is a good long-term bet? The devil is in these details.
Everyone is searching for new ways to turn data into $$$ (monetize data assets). Everyone is looking for new levers to extract value from data. But data ingesting and modeling is simply a means to an end. The end is not just more reports, dashboards, heatmaps, knowledge, or wisdom. The target is fact based decisions, guided machine learning and actions. Another target is arming users to do data discovery and insight generation without involving IT teams…so called User-Driven Business Intelligence.
In other words, what is the use case that shapes the context for “Raw Data -> Aggregated Data -> Intelligence -> Insights -> Decisions -> Operational Impact -> Financial Outcomes -> Value creation.” What are the right use cases for the emerging hybrid data ecosystem (with structured and unstructured data)?
Next best offer, next best action, interaction optimization, and experience optimization typically have similar architecture. Machine learning and multivariate statistical analysis are at the heart of these cutting edge Behavioral Analytics strategies. Typically firms use statistical tools for segmentation models, behavioral propensity modeling, and market basket analysis.
The bleeding edge in next best offer is increasingly around:
- Applying machine learning to find connections between product tastes and different affinity statements
- Developing low-latency algorithms that help show the right product at the right time to a customer
- Developing rich customer affinity profiles through a variety of feedback loops as well as third-party data source (e.g. Facebook user demos and taste graph)