(Data) Corruption Running Rife in the Public Sector
A Forrester Research, Inc. report from November 2014 (“Better Customer Relationships Require Trusted Data” by Michele Goetz and Kate Leggett) pointed out the vital role of data quality in the success of CRM delivery, which, in the “age of the customer,” is intrinsically linked to the optimization of customer engagements. This report cites modelling that shows a 10-percentage point increase in a company’s Customer Experience Index score could drive loyalty revenue exceeding $1 billion. And, having accurate customer data goes a long way in improving your Customer Experience Index score.
Clearly in the public sector, “loyalty” is not as relevant a concept, and revenue-generation opportunities are limited. What is clear, however, is the strong connection between data quality and operational efficiency in public sector organizations, with data owners fighting a continuous battle to keep that data clean and leverage the content to better serve the citizen. The Forrester report also cites direct links between bad data and employee productivity, operational costs and compliance issues.
To try to improve data quality, a minority of public sector bodies have moved to implement a centralized Master Data Management (MDM) model — all data becomes centrally managed and the organization’s systems, including the Verint Engagement Management system, become spokes to that hub, pulling data from and pushing updates to the MDM. Such projects, however, tend to be complex, costly and frustratingly difficult to get right. As such, success in this form is out of reach for many in austerity-hit organizations.
Therefore, many public sector organizations will choose to use the Customer Data Model within their CRM system as their “master data” repository. This approach works well — the data model holds the fixed and variable data about a citizen’s status and preferences, and all interaction and transactional customer history records are linked to that record as the “single view” is built up. Tools within the system can be used to detect and cleanse the inevitable duplications that occur with day-to-day use. For example, I am known as “Bob” to most (and “Dr Bob” to many). Yet, ask me a more formal question and my legal first name (Robert) comes out of my mouth! As such, I’m sure I must exist in multiple forms on many systems.
As well as data cleansing, Verint Engagement Management can also be used to intelligently extend the data model through the often-overlooked business rules capabilities of the CRM system. For example, if you are starting to use Twitter as part of your customer service program, it would be useful to capture a customer’s Twitter handle during their next contact. A configurable business rule can be used, via the secure Web portal or via a contact center agent’s desktop, to prompt the customer to supply this information.
Recently, at a U.K. user group meeting, I was pleased to hear Anna Bishop of Riverside Housing describe how her organization uses these business rules to proactively flag customer issues to their staff, not only personalizing the service for their callers but also driving checks to maintain data quality.
Improving the citizen experience is critical for government and public sector organizations–and one way to do this is to improve your citizen data. Leveraging the data cleansing and often-overlooked business rules capabilities of their CRM systems can provide a low-cost way of accomplishing this task. And Verint can offer advice and guidance on leveraging those capabilities where needed.
While it may not result in an additional $1 billion in revenue as for their counterparts in the consumer world, it will likely result in more satisfied and better-served citizens.
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