Data Management for Membership Organisations & Associations

For any customer focused organisation and for membership organisations specifically, maintaining an accurate, up to date and good store of membership data is an essential ingredient in being able to present the type of customer experience that a member expects. But keeping good data, de-duplicated and up to date is no easy undertaking unless it is planned for and built into the day to day management of membership information.



Membership data comes from numerous sources, from:



• Completed membership forms

• Details telephoned or emailed through

• Faxes received

• Business cards collected at events

• Web site form submissions

• And many other channels



So having a centralised repository for core membership data promptly becomes an essential requirement for any membership organisation. There is nothing more embarrassing or damaging to a members idea of an organisations perception of them, than being wrongly communicated to by two areas of the same organisation that hold different views of a members details. Subsequently having a clean, correct "single view of the truth" is essential.



So how do we go about getting clean data and keeping it clean? The foundation of any information management strategy is a periodic mass data cleanse exercise that takes all key data - at an company and/or individual level - and de-duplicates the data against itself and then cleans main data fields against established key reference information. To illustrate:



1. Validates addresses against the post code data file

2. Validates that phone numbers are in the right format and have the right std code for the location given

3. Validates that email addresses are in the correct format and have valid domain names associated to them



This periodic data cleanse will provide a clean base from which to build going forward.



Keeping the data up to date and clean on an ongoing basis must then be developed into business procedures and technology solutions as data is updated by membership management staff and/or by the members themselves. Providing data validation facilities at the point of data entry, whilst not impacting in a negative fashion to the data entry experience, ensures that the information entered matches data reference points. For example checking the address lines are right for a given post code, the std code for the phone number is correct, and the email address has a valid domain name. All of these "lookup" facilities are easily built into a data entry user interface - for both membership staff and members themselves - and add immense value to making sure that clean information is entered into a software solution.



Once the core data has been validated and cleansed and the record is entered to the database, it is essential to ensure that the record being added isn’t already present in the database and, hence, is being duplicated. Data de-duplicate algorithms should be configured appropriately for your exact required level of de-duplication checks to make certain that you can detect the majority of duplicates but, at the same time, don’t negatively impact on the practice of entering data into the platform. For example, you’ll need to determine which mixture of data fields should be used for a duplicate check - in most case, a blend of first name, last name, post code, first line of address, and email address are used.



Within the combination, you will need to establish the level of "fuzziness" that you’ll employ to match information - for instance, is "Dave" and "David" similar, is a minor mis-spelling of a first line of address (a common factor in web form completion) good enough and will it be able to be used for de-duplication purposes? A competent data management expert will be able to inform you on the fundamentals for such algorithms and will be able to implement them for your individual situation. These algorithms should be reviewed regularly to ensure that they are meeting your requirements.



The issue of when, and by whom, data de-duplication should be carried out should be addressed. For membership staff, should it be upon entering and saving information within the platform (i.e. at the point of data entry) or should it be a separate offline activity (or should it be a mixture of both)?



For members entering or modifying their data online then it is highly unlikely that you will ask the member to de-duplicate their own data - there are huge data protection and privacy implications of allowing them to de-dupe themselves. Consequently where and by whom, is this kind of data de-duplication to be completed? Again, your data management policy should address these factors and should be periodically reviewed to make certain that it is functioning from a data quality viewpoint and a customer experience viewpoint.



As we have observed from just the brief outlines above, there’s a fair amount to think about with regards to a data management plan. It is vital that any data management strategy is created on practical, pragmatic customer and member engagement strategies and becomes a natural part of the customer/member engagement procedures. If it turns into an insincere "add on" to these kinds of processes, then it won’t happen and your data will promptly decay and become worse than useless. A transparent, concise, common sense data management plan should be documented and adopted across the organisation. It should also be reviewed on a frequent basis as a key part of the overall customer/membership management review process. Only after that can it provide an invaluable platform for the ongoing quality management of membership data, providing the foundation for the development and implementation of all product and service offerings that your association wants and needs to provide to its membership base going forward.