As much as digital transformation involves the use of technology, it is not purely about technology, writes Gary Allemann, MD of Masterdata Management .It is about driving improved customer experiences and enhancing operational capabilities.

What this requires, more than anything, is actionable business-driven intelligence, including location-based intelligence to help organisations better understand their customer. Analytics is a fundamental component of this since data without analysis is meaningless. However, if data cannot be operationalised and integrated with core systems, it can add no value. The key to leveraging the power of location intelligence to drive competitive advantage lies in data quality and data integration.

Location data has immense business value

Location intelligence is the product of a plethora of location-aware devices, from mobile phones to GPS-enabled vehicles and a variety of IoT devices, combined with big data and Artificial Intelligence (AI) capabilities. These connected devices enable locations to be pinpointed and tracked over time, which presents incredible potential for insight.

Adding a location vector to customer analytics can provide more context that can give a better understanding of customers. Armed with this data, a more in-depth customer profile can be created, including information such as where and when they shop, where they work, if they work from an office or home, and more.

By identifying patterns and trends that may not have been evident before, insights that improve business decision making, increase efficiency and drive innovation can be derived. This insight can be used to better understand customer behaviour, grow sales, reduce risk and increase responsiveness to external events and trends.

Location data is being used by insurance companies to gauge the risk of specific properties more accurately, and by bond originators to better evaluate the value of real estate. Governments are beginning to use this information to better understand which areas of their populations are underserved in terms of access to schooling and healthcare.

Location information can also help mobile operators to more intelligently deploy 5G and optimise networks. The possibilities are practically endless, limited only by organisations’ creative thinking, and importantly the ability to operationalise this data.

Operationalising location data

The most important building block for leveraging the value of location intelligence is to have clear and achievable objectives for the data. Having a sound and concrete business case is critical to leveraging measurable benefits. Some examples include inventory planning, product development and marketing initiatives in retail and consumer-focused organisations. Other use cases include enhancing site selection processes and optimising advertising spend. These insights are all driven by location data and have specific and measurable outcomes, which will in turn demonstrate the value of continued investment into location intelligence.

It is also essential to remember that existing and legacy data still has value, and this may be augmented by location intelligence. The challenge is to merge this data, which may exist in multiple siloes, with operational data from the business, and then enhance it with location-based data. Integration tools can be invaluable in streaming legacy systems to other platforms like data lakes and data warehouses, enabling real-time updates between legacy systems and newer platforms.

Focusing on data quality and data integration to drive value and competitive advantage

It is essential to prioritise data quality. If data quality is poor, then any insights will be correspondingly poor, and if a business cannot trust data insights then they have no value. Having the right tools and systems in place to ensure data quality is critical with location intelligence as well as AI, machine learning and big data analytics projects.

The reality is that without trusted data, analytics is useless to the business. Optimally accessing, integrating and improving the quality of data is key in powering effective business decisions. Only by focusing on data quality and data integration, can data enrichment such as location intelligence be used to unlock new insights and context, with confidence in the accuracy of the results. The integrity of data is central to using location-based intelligence to drive competitive advantage.

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