Wednesday, December 24, 2014

Three Ways Your Organization Is Putting Its Data Integrity Strategy in Jeopardy

Lack of data integrity - the assurance, accuracy, and consistency of data - can harm your data-intensive, customer-oriented applications, transactions, and processes. When data becomes unreliable, everyone from customers to C-level managers question the credibility of the business-level activities that use it as justification. If a health insurer cannot trust the demographic data of a particular risk pool, for example, how can they accurately determine the premium rates the group should pay? Organizations must build an effective data integrity (DI) strategy to maximize the return on their systems and data. Let's look at some of the reasons our data integrity plans goes awry, and what we can do to resolve the problem.Migration from Legacy to Strategic SystemsA past tendency of organizations to deploy systems in a haphazard way resulted in multiple, disparate systems that operate independently without a standard framework or language. This lack of integration makes business transformation problematic. Over time, as these legacy systems are migrated to newer strategic systems, data inconsistencies, inaccuracies, and operational delays can develop; all of which adversely affect customer experience and revenue.OutagesUntimely outages may lead to stuck orders, unprocessed transactions, and bad data. For example, a bank whose ATM transaction processing suffers an outage will be forced to enter those transactions into their General Ledger by hand, risking keying errors. Alternatively, a CRM outage may mean that while and online customer transaction is made, and the payment is received, that buyer's information may not be retained for service or marketing purposes later.


System Design or Architecture FlawsSometimes, simple oversight can cause downstream problems that adversely affect the organization. System design problems create situations in which incorrect information is populated across multiple systems. Such errors might not be immediately recognizable, but typically present themselves in distinct ways... such as on the balance sheet. For example, your customer pays online with a Direct Debit option but the transaction is classified as Net 10 in the billing system. The customer may face undeserved late fees, and unwanted hassle, due to a perceived late payment.Automate to Preserve Data IntegrityThe errors and delays that result from a lack of data integrity can be avoided by employing software that automates manual business and desktop processes. Automation software works like a "digital employee"; standardizing, formatting and moving data during migrations from legacy to strategic systems. In the case of outages, the technology enters transactions into the core system or other systems of record with total accuracy, rather than taxing your traditional employees and risking errors. Automation is also used to handle transactions and other complex processes, moving information from a website's back end and into accounting, CRM, and order fulfillment systems with ease.In each of these cases, the key to avoiding a breakdown in data integrity is to ensure consistency in your data, avoid human error, and preserve the link between your integrated applications. Make automation technology part of your organization's data integrity strategy to make sure your future decisions and customer service are sound.

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