In the previous blog in this series about Keeping Data Simple, I talked about Rule number 1 and the need to implement a focused data management strategy. In the past when we rolled-out CRM systems we told our users that they had to share all their contacts. Whilst not everyone complied, many did, but what we ended up with was a system full of contacts that were only known by one person and that weren’t necessarily of strategic importance to the firm.
In this, the second in the series of these blogs, I will consider the second golden rule when it comes to keeping data simple, and that is to have a simple and objective method for measuring the quality of your data.
Rule 1 – Implement simple and objective methods for measuring data quality
Many firms are realising that they need to encourage their users to interact with the data more if they are going to succeed in deploying their CRM system across the firm. The model whereby the only role that professionals have in managing data is handing a business card to their secretary seems finally to be falling out of favour. Whilst I am sure that all of us can think of a number of users where this is still the case, most professionals are recognising that CRM technology and data is not just necessary but actually critical when it comes to informed decision making.
Look at any law firm website and in the “About Us” section you will be guaranteed to find variations on the same theme, that the firm’s goal is to put their clients at the heart of everything they do. Up until fairly recently this just didn’t translate into specific behaviours when it came to CRM. CRM was seen as a tactical and administrative process. For the forward thinking and progressive firms, that just isn’t true anymore.
So if you now at least have the foundation in place and your users are starting to see that managing data is part of their job description, the next important question that you need to ask yourself is how are you going to ensure that data quality is maintained. Not everyone is as diligent or thorough when it comes to data management as we would like them to be. Therefore, it is absolutely critical that you put measures in place for data quality and have strategies to tackle issues when they arise.
Let’s deal with secretaries first. The role of a secretary now includes the need to enter and manage data and to record meetings and activities on behalf of their professionals. Many firms have tried to measure this but the results are patchy. Some firms have built a more formal evaluation in to the annual appraisal but the input from the professional is not often more than a brief subjective comment. For this to work effectively the firm has to implement some form of balanced “Score Card”. What this means is that the 8-10 critical pieces of information that are required for the contacts that an assistant looks after, need to be regularly measured. These might include:
* Job Title
* Email address
* Mailing preferences and marketing lists
* Industry sector
* Contact details
* Relationship information
Whatever it is that your firm considers to be important, you need to have measurement in place. This is also true of the professionals, but you’re likely to want to measure different information. The professional should really be providing more intelligence about their contacts and clients not the basic information and therefore the list might look more like this:
* Strength of relationship
* Key business issues or concerns
* Areas of interest
* Potential cross-selling opportunities and introductions
* Activities and meetings
Technology has advanced considerably over recent years so the measurement of this data doesn’t need to be an arduous task. There is also a real driver for doing this as well now as more and more firms move to a formal way of measuring their professionals’ contribution to firm success.
Assuming that from the first 2 blogs you now have a much more focused data management plan and methods in place for measuring success, you need to watch out for the next in the series when we look at how to tie the gathering and management of that data to existing business processes rather than creating new processes for the sake of it.