What to Consider for a Smooth Transition to the Cloud

Data enables automation

Organizations aim to automate / digitalise their operations and this imposes significant demands on data being error-free. Particularly in environments characterized by large transaction volumes the need for accuracy, consistency and comprehensiveness becomes crucial.

Modern information technology-based automation is characterized by using data to define what may / may not happen in the process.  Successful automation minimizes the need for human intervention in the process.

Yet, a research study published in the Harvard Business Review in 2017 found that only 3% of corporate data is error-free (>97% accuracy) while some 44% of corporate data is deeply erroneous (>50% of record content faulty or missing). This also corresponds with Ineo’s experience of data analyses for our customers.

Ineo helps customers succeed in taking control of their as-is business data and developing it to meet the requirements for automation, one business case at a time.  Accurate and consistent data, contextually applied is a prerequisite for the customer’s ERP assets to actually deliver automation; the alternative being a failure of past, and future, ERP investments to yield their budgeted returns.

Delivering value from data

Cloud based information technology enables core processes with a selection of best practices and customisation of process related code is no longer done.  The customization of the application is instead done with the data.  The importance of data, but also its effect on the business process rises, with a corresponding increase in the significance of data quality.  

The challenge in implementing cloud-based competencies stems from the compartmentalization of experts and understanding, while responsibility for understanding the whole (and any cross-silo processes) defaults to the customer.  The business organization must learn to adapt system capabilities to match its own operative needs by data-based regulation of scenarios. 

This requires well orchestrated master data management in a hybrid-architecture based on a Data Platform architecture, where a number of expert services form the systems-of-entry for data.  In the same context, traditional point-to-point (P-to-P) integrations are gradually replaced by event-based interface models.

Furthermore, stakeholder expectations regarding transparency, compliance and accuracy of ESG-reporting are constantly growing, which increases demands on data governance and administration outside the coverage of traditional IT systems.

Ineo has participated in roughly 100 demanding ERP projects over the past 20 years.  Our broad experience forms the basis of our competence to apply technology and find solutions with a comprehensive view of the overall process.  The need to resolve customer challenges in master data management (MDM), application data management (ADM) and Data Analytics in multi-system environments, and to enable automation is common to these projects. 

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