360-degree Customer (Citizen) View

Technology can often be the key driver in business transformation. Without technology adapting, it can be hard to drive operational or business transformation. One key technology achievement is the ability to understand your customer across all your business systems. Often referred to in business as the 360-degree customer view, or the golden customer record, is a methodology of aggregating data about a specific person or entity, normally a customer, from various systems that record interactions within the business, such as sales, service and communications. Understanding your customers allows you to predict and plan with strategies based on pure analytics about your customers and business, but this data can also allow you to unlock suggestions to help with both operational and business transformation.

In the work we do at Arcus Global we are striving to build exciting, flexible products that allow an organisation to have one record representing a citizen, that is shared across different software applications. Nearly all of our products are designed for public sector organisations, so one record for Mr Smith can be referenced in our Built Environment, Regulatory Services, Housing, Health and other products.

This means at a strategic level, business intelligence reports and analytics, can easily be produced; and now as companies begin to utilise automation and decision making technologies like artificial intelligence or predictive analytics a business can begin to predict what future interactions or actions with a customer are going to happen.

For example, if a citizen has informed a council that they have moved house, what about updating details in the education management system to see if the children are in the correct catchment area for their enrolled school. Does the council need to look at building schools in areas of increased new development? If residents have a history of missing the first council tax payment after moving house what about predicting this eventuality and sending reminders to the citizen, pre-empting but helping prevent them from missing the first payment.

Achieving the golden record can be difficult, often businesses and government organisations have lots of separate disparate systems running on a multitude of platforms and architectures. To reach the stage of having a golden record often requires an architectural oversight and data analytics strategy, to combine structured data, such as information in databases and unstructured data such as social media, letters and documents. Systems will often need integrating, which will require API’s to enable applications to share data and communicate with each other, and other platforms, to enable data sharing and a cohesive, up-to-date, accurate view of customers.

In some cases, legacy applications can be converged by replacing them with new, modern, application residing on one platform, allowing for data to easily flow between applications. There are also other approaches that can be used, such as replicating databases and overnight data synchronization between systems and databases. Data quality and data cleansing practices are key to ensuring that once systems are integrated we can attain an accurate picture of customers. Data needs to be accurate, not duplicate or conflicting, and so forth. This can often be challenging when previous legacy systems have allowed for multiple records representing one entity to be created, it can often be very challenging to match these records to a single entity when legacy systems have not validated data entered by users. Often I have seen data from legacy systems where a customer has been entered as Mr Smith living at 123 The High Street, it can be difficult without more data to understand if this is one Mr Smith living at the address that has been entered into the system multiple times, or Mr Smith and his ten sons are living at the address, so rightfully there should be ten Mr Smith’s!

Integrating systems helps us get closer to the concept of the golden customer record, but these can often be complex projects and without correct configuration and architectural oversight you could easily end up with corrupt or inaccurate records, or even completely broken integrations.