Data is the Currency of Competitive Advantage

Utilising your data correctly can give you a strong competitive advantage

Since the mid 1990’s with the advent of data warehousing and business intelligence there has been a growing awareness within businesses of how important data is becoming, so much so it is now considered an asset. Throughout the 2000’s while many organisations were cutting costs in IT, customer relationship management and business intelligent systems were not cut as companies realised they needed to better understand their customers and prospects. More recently social media has increased the need for businesses to understand and engage with their customers continuously in real time. It has also generated rapidly expanding, previously unheard of volumes of unstructured, multi-media data that records those interactions.

To understand and take competitive advantage of this new critical asset companies must simultaneously take advantage of several emerging technologies and develop a customer facing culture. This is no easy task and there are several issues to address in any data strategy that seeks to make these changes:

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Data Quality is the most critical issue organisations face in their data strategy.

They may have neglected their data for years taking for granted that their transactions served their basic purpose regardless of the age of the legacy applications. However, when they attempt to use that data in a reporting and researching context it is no longer fit for purpose and must be cleansed before it can be used. This can greatly extend the elapsed time of any strategy and multiply the cost.

Data Management and Governance best practice is essential to any data strategy.

Typically, a large company will have several copies of the same data in different siloed applications. The data strategy depends upon the knowledge of those data elements that the organisation absolutely depends upon and which applications contain the highest quality, up to date and authoritative version of that data. The core data elements must be identified, documented, audited and classified for quality, accuracy, integrity, privacy, confidentiality and much more.

Business Strategy Alignment must be considered in any data strategy.

The data strategy must focus upon the data elements that matter to the vision, goals and objectives of the corporation. It is typically too costly to cleanse all of the data within an organisation and to do so to the wrong data will be unproductive. Investment must concentrate upon that data which the organisation depends upon to compete and fulfill its core competence functions.

Change Management will be required to support and train people as they adapt to new ways of working to manage their own data.

The business must adopt responsibility for the quality and integrity of their own data appointing data owners and stewards to be active in these new responsibilities.

Cultural Change is necessary at all levels of the company.

Managers must adjust to making decisions based upon the information rather than on gut feel. Governance practices require decisions to be open, transparent and collegiate rather than one person’s autocratic decision taken behind closed doors. Personnel who understand the business and market of the organisation must learn to recognise patterns in their data that can be useful even when dissociated from any apparent logical cause.

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Data Compliance is increasingly demanding data to be managed, reported, maintained and retained accurately to meet industry and governmental standards.

The bar is continuously been raised with new data provision impositions upon corporations.

Technology Acquisition is required to enable increased volumes of data to be held and processed for reporting.

Historically that data has been structured into relational database management systems (RDBMS). More recently, social media has forced the additional use of unstructured multi-media data in text, video, audio and graphics formats. New technologies are emerging to enable these structured and unstructured data to be analysed together in large volumes within business intelligence and data analytics.

New techniques, skills and practices are required to do this successfully. Companies cannot buy the technology and use it as if shrink-wrapped. A full enterprise strategic approach is required that encompasses at least the basic issues mentioned in this brief article and much more. The company will typically not carry the necessary expertise internally and will require external advice, support and assistance from specialised industry expertise.

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