Whether its enterprise solutions, data warehouses or big data platforms, the data strategy is very similar. Information is 'harvested' from existing data sources and is ultimately reconstructed to provide business insight.
Outside of greenfield projects and major upgrades, the data strategy is usually considered in the final mile. It's also regularly positioned as an assumed benefit that is shadowed by operational and strategic benefits already achieved.
Enter the Street Light Effect
David H Freedman coined the term which people only tend to look where it is easiest (i.e. under the streetlight even though they lost their keys in the dark). We tend to use the data that was created for other purposes and assume it can be restructured to provide another dimension of knowledge.
Some examples of where this is done today:
Customer Behaviour - is derived purely from transaction history and assumed demographics (not on the actual behaviour of the shopper). A customer can spend 30+ minutes browsing and evaluating a shop's contents. However we only really understand which products were extracted from shelves at the checkout.
Employee Retention - is measured on tenure, exit interviews and performance feedback processes.
Campus/Office Utilisation - is generally measured by overall campus access and/or predefined schedules e.g. meetings times, lecture hall bookings etc
Performance Optimisation - Are measured by throughput, total cost of manufacture and qualitative checks at points of assembly
Prediction of Future events - Are generally derived from historic events and, leverage regression techniques or spatiotemporal models for location-based prediction.
All of these have one similar characteristic. These data sources are already in place and serve a different mission to business insights listed previously. As a result we tend to search 'in the light' because there are no other available data sources.
Enter Video Analytics as Real-Time Data Source
What if you had a whole new class of data source that can be readily implemented to bridge these gaps in your data strategy?
Video Analytics can provide these new data sources. Data is extracted from video streams and ingested into your data lake. These can be leveraged to paint a greater picture of real-world interaction. By combining these new sources with existing data sources, we can provide insights as determined by your required business outcomes.
Consider Other Real-World Sources from IOT
Other new data sources for business insight may include solutions such as face recognition, geo-location based Apps and IOT sensors. These can provide identity, presence and real-time sensor feeds.
Now Leverage this Sources to Transform Your Organisation
Customer Behaviour let's redefine the customer journey by starting when they create a shopping list on an in-store app with geolocation. The App also provides a 'pick list' for when the customer arrives at the supermarket. By measuring the customer's via Hitachi's 'Activity Visualiser' (actual route, deviation from suggested route, dwell time and many others) a new profile of shopping behaviour along with store utilisation is provided. This results in a significantly richer insight than transaction data alone.
Employee Retention - identifying a 'mega-trend' such as employee churn at 18 months is easy to locate but understanding why can be more difficult. Facial recognition to understand how employees utilise the campus. A 'Company App' can be deployed to give insight as to how employees are interacting with each other. Employees at risk will tend to disassociate. One organisation was able to correlate the reduced amount of supervisor/employee time with employee churn (supervisors thinking less time spent was a positive reinforcement yet had the opposite effect)
Campus/Office Utilisation - Understand real-time campus utilisation with people counters in/out of each room. Facial recognition in situations where you want to verify attendees in a room.
Performance Optimisation - By correlating visual activity analysis with production check points; exceptions, defects and slow downs can be associated with the actual real-life events. This supports real-time optimisation techniques in contrast infrequent process reviews. This provides lead indicators that can be modeled for predictive intervention (e.g. maintenance, replacement etc).
Existing data sources are instrumental in providing intelligence, but, don't be afraid of constructing new sources to enrich, evolve and (potentially) disrupt your business insight.
What other business insights and enablement would you expect from video analytics??