In previous posts, we described why a source system is not as accurate as companies might like to think. We demonstrated that source systems always have data anomalies. Based on that we know BI systems present wrong information, we discussed what types of anomalies usually exist and deliberated what their impact on business might be. Accurate data provides management with a reliable and trusted source, which in turn helps develop confidence in decisions made based on that source data. The bottom line is that accurate data and management of data anomalies support business scaling and growth.
Check out TripleCheck to learn about data monitoring and management solutions.
Data anomalies management allows for for company to growth
When companies manage their data anomalies and other data problems, they can look forward to:
- Growth without loss of data control
- Data accuracy reflecting business flow
- Management and control of user activities and permissions
- Easy implementation of regulation procedures
- Fraud prevention
- Finding hidden money
To manage real and effective data flow, companies need the following capabilities:
- Data anomalies management of all source systems in one place – Ability to decide the importance of an anomaly regardless of a specific source system.
- Prioritize anomalies and anomalies’ assignments.
- Consolidated data anomalies review and control – Ability to approve specific data or specific logic/ rules of data with confidence, preventing repeated reviews of the same data.
- Historical data review and comparison.
Accurate and healthy data facilitates business growth
If a company plans to have a healthy growing process, it must have control of its enterprise software/ source systems data.
Business growths calls for new needs and services to be implemented and integrated into existing company source systems. Adding CRM, ERP and other applications with multiple modules and multiple layers – all of them with permissions and activities from different aspects can cause the company to lose control over its source systems data.
The problem is much more important when dealing with multiple cloud applications. Data decentralization makes this issue even more complex, enhancing the need to control the data in one unified place even if it is located and divided between various on premise and cloud source systems.
When businesses grows, it is essential to record and manage data anomalies in one place with a unified format. Management of data anomalies is done by setting rules and policies according to business procedures, priorities and users. To do this, companies require data output analysis with enhanced capabilities, maintaining control of the ever growing and expanding data. Business growth creates a scaling in user permissions and activities that must also be managed. Data management is required so that in the long run growth does not cause the company to lose money.
Check out TripleCheck to learn about data monitoring and management solutions.
TripleCheck enables pro-active data anomalies management
TripleCheck is a software service designed to do just that. TripleCheck consolidates data anomalies management into one place. It can detect data anomalies such as duplicate entities (suppliers, customers, invoices, items, etc.), negative inventory balances, abnormal costs and currency rates, weird prices and compliance problems. It bridges the gap between different systems, ERP, CRM, and other software’s data sync.
TripleCheck guarantees it clients more accurate data, better efficiency and more confidence to rely on the enterprise data. With TripleCheck, companies can enhance the control of their data, improve procedures and make better decisions. At TripleCheck, we take data anomalies management even further with our “Management by Exception” concept, in which we monitor anomalies and use this new data view concept to improve processes.
TripleCheck enables its clients to become pro-active by using data anomalies management. Double checking your data is not enough, you need to TripleCheck it.
To learn about the concept of pro-actively managing decisions by monitoring data exceptions, read our next post.
