The concept of Master Data Management isn’t something new, yet it is needed now more than ever. As marketers in the 21st century, there are a multitude of tools available to us.
These are the days when Machine Learning, Automation and Artificial Intelligence (AI) have reached a point where we can apply them on our data-sets.
We use them to manage messages across channels, find new prospects, study behavior of leads and even sell a lot better. I could go on to say that with the rise of Big Data, Business Intelligence isn’t a problem either.
The problem we face now is data. No, not a lack of it, but rather, too much of it – in too many places.
Data, and its fragmentation
Marketing trade has seen the rise of a lot of tools, such as Marketo, Salesforce, Demandbae, etc. They are what I call ‘purpose-built’ and have excellent stand-alone features. While they boast of having data management features, the ‘management’ only happens within the application.
The greater the number of tools, greater the problem of fragmentation. Data exists in too many places. The change in this data, when done in only one place, makes the entire database incomplete, inconsistent and disconnected.
Extend this across the number of applications used; we lose the ability to leverage all that we know about a channel, campaign or customer. This results in what I call ‘generalized’ offers, deteriorating customer satisfaction.
Loss of Consistency and Data Traps
Due to a limitation on the number of resources and historical development, data is fragmented across the entire database which creates ‘Bad-Data-Points’ as well as various data traps.
For example, the presence of typos in ‘zeroes’ in a series. Bad data can occur for a spread constructed by subtracting a two-time series that might be individually reasonable, yet constructed with methodologies that were inconsistent.
Impact
It’s also common that proxy spread index data is used for a particular spread, either because the data doesn’t exist, or the number of spreads is too great for the risk model to handle explicitly.
All of this results in a loss of consistency, resulting in business data getting ‘siloed,’ even if the employees are working efficiently.
Finance Operations
A recent report indicated that out of 380 CFOs, 90{ed162fdde9fdc472551df9f31f04601345edf7e4eff6ea93114402690d8fa616} are crippled with financial data. This results in delays for top management to make critical decisions.
Finance teams spend over 80{ed162fdde9fdc472551df9f31f04601345edf7e4eff6ea93114402690d8fa616} of their time gathering the data and then cleaning it. However, they only get the remaining 20{ed162fdde9fdc472551df9f31f04601345edf7e4eff6ea93114402690d8fa616} to actually build strategies.
Finance needs operational support. Another thing it needs is less fragmentation and copied data. A copy results in old data being used again and again, which has the potential to increase losses and inaccuracies in the end product.
The Bottom Line
The data your company holds is exclusive your company. No other marketer or company can replicate it. That being said, you cannot overlook the importance of building a strategy that manages that data.
The end-to-end enterprise data has a lot of value and is pretty powerful in transforming the value you deliver to your customers.
Sources:
https://leapfin.com/blog/future-of-finance-is-finops/
http://www.imf.org/external/pubs/ft/fandd/2012/09/straight.htm
http://it.toolbox.com/blogs/itmanagement/six-ways-to-handle-fragmented-data-76669
Writer notes:
Pretty vast topic. Just tried to touch it, as this article is a sample. 🙂
