Defining a data management strategy

October 2021  |  FEATURE | BOARDROOM INTELLIGENCE

Financier Worldwide Magazine

October 2021 Issue

Data is one of the most valuable corporate assets. Driven by the next generation of companies, such as Google, Amazon and Facebook, among others, data has become the basis of competitiveness, productivity, growth and innovation. In isolation, however, it is worthless. If companies want to optimise their business, they require a coherent, effective data management strategy. Those that neglect their data management strategies may find themselves left behind.

To properly utilise data, companies need to understand the ins and outs of data management. In essence, data management is the function of planning, controlling and delivering data effectively within an organisation. It encompasses the whole data experience within organisations, including the capture, storage and transformation of data, as well as its transfer between different systems and use cases. Data management requires companies to develop and execute plans, programmes, policies and practices that protect, control, deliver and enhance the quality and value of the data they handle.

High-quality, well-maintained data can boost company revenues, reduce enterprise costs and complexities, contribute to risk management and support regulatory compliance efforts. It can reduce potential errors and other risks caused by bad data, as well as increase organisational efficiency and improve data access.

Companies are creating and processing more data today than ever before, which creates challenges and opportunities for enterprise data management systems. In 2020, businesses were on track to create and capture 6.4 zettabytes of new data, according to IDC. Productivity data – which covers operational, customer and sales data and embedded data – is the fastest-growing category of new data. By 2024, IDC expects that 51 percent of enterprise data will be stored in the cloud.

Failure to implement an appropriate data management strategy can have significant consequences. When it comes to data governance, customers expect, and regulators demand, more of businesses and their compliance teams. Data loss, for example, may result in fines and negatively impact the company’s reputation.

Companies without effective data management may find themselves having to make sense of large quantities of inaccurate and disparate data, which in turn can lead to data silos, loss of business and potentially even loss of data itself. Human error, employee negligence and theft are risk factors which companies need to manage. A long-term approach to data management is required, or companies risk losing value.

Data management must be integrated into the fabric of the company’s operations and culture. Implementing a strategy should begin with a data management system which monitors data collection, processing and management. Technology such as artificial intelligence (AI) and machine learning (ML) can be helpful, but deploying these solutions may be a challenge for those with legacy systems, where data is stored in outdated or disparate silos.

It is also important to consider the relationship between data management and business objectives. These objectives should inform data strategy, to prevent the organisation wasting valuable time and resources collecting, storing and analysing the wrong types of data. Companies should ask: What are the overall objectives? What data is required to meet those objectives? And what types of insights and information are required to make progress toward these objectives?

A data strategy should be both offensive and defensive. Companies should establish clear business goals to set the context for their data strategy and ensure it delivers what the business really cares about. Equally, companies must achieve business-wide buy-in for the strategy. Patience is key, as developing and implementing an effective data strategy can be a gradual, long-term process.

There are practical steps companies can take to protect their data. Companies should clarify who in each department has a critical role in data usage and grant appropriate access permissions to staff. It is also prudent to identify where walls and other safeguards around sensitive information should exist to prevent unnecessary disclosures. Permissions must be regularly reviewed, as users change over time, moving departments or leaving the organisation.

Data management will continue to occupy companies and their senior leaders for the foreseeable future; likewise, data incidents will persist. Despite many companies investing in data management, problems continue to grow. Some companies still perceive data as solely an IT issue. To truly benefit from the vast quantities of data companies are capturing today, it must be treated as a corporate asset. Maintaining the best data management and governance practices will assist companies in preparing for potential threats and capitalising on the opportunities that data presents.

© Financier Worldwide

BY

Richard Summerfield