Does your data strategy support your business goals?
By Gary Allemann, MD at Master Data Management
Big data and the data explosion are terms that have become industry buzzwords, and have led many organisations to hop on the bandwagon without considering all of the facts. The reality is that big data does not simply refer to data volumes, but also to the unstructured nature of the data and its source, typically social media. Data is increasing at an exponential rate, which does present challenges, and big data can provide business insight. The question that businesses need to ask themselves however is “which big data do I need” or even “do I need big data at all”. Answering these, and similar, questions requires a sound data strategy, and more importantly a data strategy that is aligned with and supports an organisation’s business goals.
Organisations today are experiencing something of an information overload, and in an attempt to keep up, many enterprises join in with the big data hype without fully understanding the data, their business, and the big data’s place in their business. This unstructured data generated by social media tools can help businesses to understand what their customers are saying about them. However it is scattered through various media across the Internet, and traditional data tools are simply not equipped for this.
The cost of gathering and analysing this data needs to be weighed against the benefit it will provide. In truth, for many organisations, this equation means that big data is not yet relevant and will not add any value, so spending large sums of money on big data initiatives will prove to be a waste of time and money.
Added to this, the big data phenomenon and the data explosion offer additional challenges. Attempting to manage, measure and monitor absolutely every scrap of data often leads organisations to become overwhelmed, leading to complete inaction with regard to data, or ineffective management of multiple data sources. This can end in the proverbial “flooded with information but starved of knowledge” phenomenon affecting so many businesses. Overcoming this phenomenon requires data to support the business and its goals. In order to leverage any real benefit from data, it is vital to have a data management plan or strategy, but more than this, it is imperative that data management plans are linked into and support business strategy. This will help to ensure that any data that is measured and monitored will add business value and go towards improving the bottom line. This approach also ensures that resources, time and money can be focused on delivering information that will have the biggest positive impact on the business.
In an increasingly data-driven world where complexity is only increased by different types of data, increasing volumes of data and multiple regulations and guidelines governing the use and management of data, a data strategy is critical. A business driven data management strategy helps organisations to achieve three principal objectives. It ensures that data initiatives are aligned to business needs and focused on business priorities by achieving data excellence and information management. It ensures that operational efficiency is improved by helping businesses to identify and increase key business process failures that cause poor data quality. Finally it helps to reduce risk, by ensuring that a pragmatic information risk management strategy is developed and maintained.
Ultimately a business is driven by the principle of creating shareholder value, and data needs to support this. If data is not delivering value, then it is not worth spending money to manage it. In order to ensure that data does deliver value, a sound understanding of the business goals and strategy, linked into data management plans, is critical. The data excellence framework describes a proven methodology, processes and roles necessary to achieve a business-driven data management strategy that will help businesses to ensure that data is manageable and that, more importantly, value can be obtained from this data.
