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Archive for July 7th, 2009

During tough economic times, CFOs are tightening the belt and are looking into managing expenses across organization; in order to achieve necessary cuts in the expenses they recruit help from all business units/division/areas within the organization. Managing expenses is enterprise wide tasks and CFOs (Chief Financial Officers) lead this initiative. Impact of managing expense is far reaching; it helps organization to impact profitability by reducing expenses.

I believe that data quality is an enterprise level challenge as well; data quality affects all the parties who use, generate or maintain data for the purpose of managing their business. Typically CIOs (Chief Information Officers) lead (or should lead) all initiatives associated with data quality and they should look for recruiting help from across the organizations (just as CFOs or CEOs do). Creating enterprise wide awareness and urgency about the impact of the issues associated with data quality (and hence information quality) will ensure success and proper level of sponsorship of the data quality initiatives within the organization.

While there are several ways in which impact of the data quality can be highlighted to the organization, following are some practical examples which I have found to be easy to use while communicating soft ROI or impact of data quality on individual business units.

Sales Organization:

Capturing good quality data would directly impact on helping to close additional deals or help with closing of the deals which might have been lost otherwise. While this is a broader statement, I can give few examples where this has helped me in realistic situations….

Capturing Win/Loss reasons consistently on deals sales team marks as closed (Won or Loss) would result in better analysis of reasons why organization is losing deals. Based on this information, sales and sales operations organization can always recruit help from marketing or engineering to overcome reasons behind the losing those deals. Many times once better understanding about why deals are being lost against a competitor or lost in industry vertical is well established, minor tweaks in positioning or minor product enhancements could turn the tide and will reduce loss of deals in those situations. Of course all this will be possible if good quality data about win/loss reasons is captured. In order to make sure that this data is captured on an ongoing basis, Sales Operations need to commit to investing time on monitoring capture of Win/Lost reasons. They also need to figure out if there are standardized templates they might want to use to capture this information succinctly.

Another example in similar category would be to capture the competitor information (Competitor name, name of the products being competed against) on all deals. Better analysis of the win/loss data against competitor can help with recruiting marketing/engineering help to fend off competition. Again what it takes is qualitative data about competition and products in every deal in which sales is competing.

Interesting thing about this is that one or two deals (off-course depending upon your ASP) salvaged could pay for entire incremental expense of enterprise data quality initiative for the year or so.

Marketing:

Amongst many aspects, marketing department budgets and effectiveness is decided by how many sales qualified leads are generated on periodic basis. In many instances, speed with this Marketing is able to nurture and grow leads to be sales qualified leads really depends on the quality of the information captured. These days marketing automation tools provide personalized messaging but for that messaging to work marketing really needs to gather quality information about leads. It’s relatively easy to justify effectiveness of marketing campaign or even lead nurturing process by considering data quality of the leads data. For example, a client of mine decided to market their product to clients who had ERP system installed in-house (SAP or Oracle Applications). Unfortunately, lead data which was captured through webinars and trade shows did not capture this information in a consistent format; on top of that this field had a lot of data quality issues (free form text). Investing marketing and IT time to clean this data would greatly increase the effectiveness of any campaign or lead nurturing program to be run against these leads.

Operations and Finance:

If finance or operations team is particular about capturing all the contract and customer/account details in a clean way first time around on the transactions, they can save time it takes to ship and then bill the products to customer (save time wasted on figuring out where to ship/where to bill etc…), thus saving several days on shipping and invoicing clients. This will directly result in improved cash flows (early billing = early countdown of terms = early payment), greater customer satisfaction etc…If the data on existing contracts or existing customer is not clean and if your organization is engaged into business of reselling into those accounts or on renewals, it is worthwhile to make an effort to ascertain data quality of this data and save several days it takes to go through shipping and billing process.

In summary, I believe that data quality is enterprise wide issue which impacts almost everyone who creates uses and maintains data generated through business operations. CIOs need to champion the data quality cause at enterprise level just the way CFOs or CEOs champion the cause of cost cutting across enterprise by enlisting help from each and every department. Some of the ideas given above can be used for highlighting softer ROI of data quality across enterprise. Details and specifics of the above examples will vary from organization to organization based on the business they are in and the business model they have within their organizations.

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