Automation Potential in: Customer Data
today's Challenges
Customer master data sits at the core of every organisation, and yet many struggle to ensure that data is easily found, accurate and only shared with those who need it.
Customer data is a complex area for any organisation. It was only a few years ago with the roll-out of GDPR that most businesses realised they were keeping inaccurate and out of date information. Despite this recent cleansing of records, data can stagnate quickly.
automation Impact Evaluation
Multiple contact points: Keen to update their customer data, many organisations check and verify with customers that the information they hold is correct. This data can come in through a wide variety of formats. It could be that a customer phones a branch and a member of staff writes down new details on a piece of paper, a salesperson takes details and logs them in the ERP, or the customer enters new details through an online chat tool. Customer data comes in through a wide variety of disparate systems, each with different people who have access to the information. One of the major advantages of Robotic Process Automation is that it can work across several different systems and gather information onto one platform, saving significant staff time and effort.
Standardised data entry: The quality of data can vary where different people are capturing and inputting data in different ways. In order to reap the benefits of RPA it is important that standardised fields and values are established so that a bot can then quickly extract that data. Automation can help ensure a standardised process is in place for the creation of customer records, whilst reducing the manual process of copying and pasting data from one system to another.
Duplicate records: When it comes to customers, duplicate records can be more difficult to identify. Multiple records may exist where a customer has moved location, visited different branches or the customer has set up a new account as they have forgotten their old details. With a large amount of customer data to go through, a simple comparison is not always feasible. RPA can be implemented to carry out a full search of records and identify matched names/address and contact details for an employee to review and choose whether to aggregate or delete the data.
Regular schedule: Putting in place robust governance around data requires regular review of the data being captured. This is one of the key ways in which automation can support. Instead of scouring through your entire database every six months, a ‘bot can be run overnight to search for potential errors, missing/duplicate data and create a report for an employee to review in the morning. This can significantly save time, keep you on top of any regulatory issues and free-up an employee to focus on higher-value work.
case Study
Accident Claims Lawyer
An accident claims lawyer with multiple locations needed a way in which to streamline their existing/archived customer database to comply with GDPR regulation. Much of the existing data was sitting in geographical silos and the time.
We implemented a bot which was able to take information from the silos, structure it in the same format and place it in a central archive which was located on a secure cloud. We then created an online form that clients could fill in so as to request their data. Our bot would check the central archive and automatically create a word document with all the details held for that client. If the client wished to delete their records, the bot could then do that not only in the central archive but the original silo too.
We significantly sped up this process with a 95% reduction in processing time and 0% error rate.