In today's information economy, businesses have the opportunity to collect and analyse an increasingly vast array of customer data through their Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP) systems. But what steps can they take in order to reach that single-view nirvana, asks according to Mark Dunleavy, UK managing director fro Informatica.
Here Dunleavy explains the ten major factors involved in achieving this goal, ranging from knowing where your valuable data is actually being kept, through to understanding how each piece of data fits into your overall strategy, to keep data in check throughout the whole organisation, and of course knowing what to do with it:
- Know where your customer data is
Most businesses have huge budgets for working out how to collect customer information, yet very few have actually used this abundance of information to achieve ROI. Don't make this mistake. If not all of the valuable customer data is in the system the sales team accesses, and the biggest way of building revenue in the business is sales, alarm bells should ring.
- What aspects of data make up the master record?
Knowing where the most complete and up-to-date data resides is half the battle. However, this data is often not just in one place. For example, the ERP system may be the master record for financial data, but is likely to contain very little on the everyday customer relationship. The CRM system, on the other hand, might be the solution for everyday contact data.
- Choose the right platform
To achieve a single customer view, a decision must be made over the right platform to share it in. It's important to make a decision on whether the platform will be hosted on-premise or in the cloud. Important data sources such as big data and social media must also be considered when choosing the platform the business will operate from, as in three years' time, every platform will most likely mandate their inclusion. Whatever is selected as the final platform, user visibility, access and data privacy must be considered. This will ensure that it's a system users are already accustomed to working with, and that it conforms with both data privacy and protection.
- Synchronise data with business systems
When a system is chosen, it's essential to look for a solution that is easy to configure and can adapt to changes in data governance. Look for a solution that can be configured to synchronise updates rather than just running a 'scheduled dump'.
- Make sure John Smith, Jon Smith, and Jonathan Smith are one record!
One of the biggest pitfalls of any customer-centric project is duplication. Variations in names and contact details can result in duplicates slipping through routine checks. An initial profiling of sample data can help a business work out patterns in duplicates.
- Be reactive and preventative
Data quality is an issue that businesses do not tend to tackle until it's already a problem. They fail to put best practices in place before dirty data and duplication have rendered their database useless. Look for a solution that offers the flexibility to match business needs and which can be easily embedded into the chosen platform.
- Make sure data is up to date and complete
Ensure that many data gaps as possible have been plugged. Use a solution that can update old data and insert new information when needed, or a solution that can match existing records with purchased lists.
- Build a culture of ownership
The easiest way to achieve this is for salespeople to own their accounts and ensure they keep each and every one of their own customer records up to date.
- Standardise data for better reporting
If reports rely on a number of free text fields that have not been standardised, the business may encounter issues when running a report on sales performance. By standardizing the data, it will become clear what may have slipped through the cracks in previous reports.
- Don't opt for a 'quick fix'
A one-off cleanse and de-dupe may solve an immediate problem, but it doesn't tackle the issue from the source. If the problem lies with poor data governance, ineffective use of applications, or lack of ownership of the data, a quick fix today will be a complete waste of time in the longer term.
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