I’ve never been one to believe in horoscopes, but when it comes to deploying successful CRM in professional services firms, I’m definitely a Libran. You see in the end it’s all about striking the right balance. Technology has moved on so much in the last few years that there are now so many choices open to firms on how they execute successful CRM programmes but there are some critical workstreams within the project where the project team really have to achieve that all important balance. In this, the first in a series of blogs on this topic I am going to explore some of the issues and challenges around managing your data.
Data Quality versus Speed of deployment
The received wisdom has always been that you must clean up your data before you put it in to the CRM system. In fact that’s always been my opinion, but my experience has led me to realise that there is more to it than that. For example I don’t think many firms have had a great deal of success in trying to get their professionals to clean up their Outlook before the CRM system is launched. The truth of the matter is, you are either the kind of user who believes in having good quality and complete contacts in your Outlook or you’re not. If you are the former then your contacts will already be clean, if you’re the latter then you’re not going to clean them up just because a new CRM is coming.
The other issue is that taking a controlled approach to a user’s contacts during the synchronisation can really hold up the speed of the roll-out. So the alternative potentially worth considering is, is it better to sync everyone’s contacts as quickly as possible and then deal with them once they’re in the system. To decide which is the right approach for you, you need to consider the following questions.
- Can I secure senior support within the firm to get users to accept the fact that during the roll-out there will be a temporary period of poorer data quality?
- Can I implement a process for evaluating the importance of contacts once they’re in the system so that I can archive the contacts that aren’t worth cleaning up?
- Can I get the firm to agree to an “Opt-out” approach to contact sharing and not an “Opt-in” so that we can automatically harvest their contacts and not wait for them to share them?
Depending on the answers to these questions it might make more sense for your firm to move towards a more automatic approach to data quality management.
For those firms who have already launched CRM and are still having issues with managing their data, the balance that you have to strike is trying to manage your data centrally versus decentralising it. For years firms have argued that managing data centrally leads to improved quality, my experience is that this is only partially true.
Central teams might be able to keep on top of managing company names and addresses, but ultimately their success is dependent on the amount of data stewards that they have and the automation that they have in place. Most firms simply don’t have enough resources to manage the data centrally so the questions you need to ask are:
- Do we have enough resources to manage everything? If not then you need to take a focused approach to managing your data and only manage contacts and clients that are the most important.
- Should the role of our steward be “re-checking” other peoples’ work? For firms who have change control systems in place for their data, very often end up simply re-checking changes other people have made. If they weren’t doing this they’d be able to spend time doing more valuable tasks.
- Can we change existing processes to contribute to the information being managed in CRM? A really good example of this is changing the new business intake process so that it’s actually 2 different processes. Risk and compliance elements which is an administrative task, and then client intelligence gathering e.g. why did the client choose us, where did the work come from, what are their other business issues, which is a business development task
Ultimately firms will not be able to get to the top right hand corner of the diagram unless they make some changes to the way that they gather information. To achieve the perfect balance when it comes to data management, you need to ask yourself. Do we need a particular piece of information? If the answer is no, stop. If the answer is yes then ask yourself, can we gather this data from an existing process or by implementing automation? If the answer is yes, then you can improve your data by implementing technology or process change. If the answer is no, then you need to ask yourself who is the most appropriate person to provide this data?
By evaluating your information processes in this way then you are ultimately much more likely to strike the perfect balance when it comes to data management.