As the world becomes smarter, data is becoming the key to competitive advantage, meaning that a company’s competitiveness is increasingly determined by how well it can harness data, apply analytics and adopt new technologies. According to the International Institute for Analytics, by 2020, companies that use data will achieve a $430 billion productivity advantage over competitors that do not.
It is clear, therefore, that data is now a key business tool, revolutionising the way companies in most sectors and industries operate. Indeed, every business, regardless of size, should be a data business. And if every business is a data business, then every business needs a solid data strategy.
Everything starts with a strategy
Instead of starting with data, every business should start with strategy. At the beginning, it doesn’t matter what data you have, what data you already collect, what data your competitors collect, or what new forms of data become available. It also doesn’t matter whether your business has mountains of data available for analysis or almost none at all. A good data strategy is not about what data is potentially available – it’s about what your business wants to achieve and how data can help you achieve it.
So, if companies want to avoid drowning in data, they need to develop an intelligent strategy that focuses on the data they really need to achieve their goals. For data to be truly useful from a business perspective, it must meet a specific business need, help the organisation achieve its strategic goals and create real value. This means identifying the key challenges and business-critical questions that need to be answered, and then collecting and analysing the data that will help answer them. It is also important to note that none of the data types are better than the others. Using data strategically means finding the best data for your company, and this may be very different from what is best for another company. With so much data available these days, the trick is to focus on finding the exact, specific pieces of data that are most useful for your organisation.
Key elements of a good data and analysis strategy
- Your data needs – To find the right data, you first need to define how you want to use the data. For some purposes you may need certain types of data, for others you may need other types.
- How to get and collect data – Once you have identified what you want to achieve with your data, you can start thinking about how to get and collect the necessary data for your business needs. There are a number of ways to obtain and collect data, including accessing or buying external data, using internal data and introducing new data collection methods.
- How to turn data into insights – As part of any good data strategy, you need to plan how to apply analytics to the data to gain business-critical insights that help decision-making, improve operations and create value.
- Technological infrastructure requirements – Once you have decided how you want to use your data and what types of data are the best for your company and how you want to analyse that data, the next step in creating a solid data strategy is to consider the technological and infrastructural implications of those decisions. This means deciding on the software or hardware that will use the data and turn it into insights.
- Data skills within the organisation – To get the most out of your data, it is essential to develop certain skills. There are two main ways to develop data skills within an organisation: strengthening internal talent and outsourcing data analysis.
- Your data needs – To find the right data, you first need to define how you want to use the data. For some purposes you may need certain types of data, for others you may need other types.
- How to get and collect data – Once you have identified what you want to achieve with your data, you can start thinking about how to get and collect the necessary data for your business needs. There are a number of ways to obtain and collect data, including accessing or buying external data, using internal data and introducing new data collection methods.
- How to turn data into insights – As part of any good data strategy, you need to plan how to apply analytics to the data to gain business-critical insights that help decision-making, improve operations and create value.
- Technological infrastructure requirements – Once you have decided how you want to use your data and what types of data are the best for your company and how you want to analyse that data, the next step in creating a solid data strategy is to consider the technological and infrastructural implications of those decisions. This means deciding on the software or hardware that will use the data and turn it into insights.
- Data skills within the organisation – To get the most out of your data, it is essential to develop certain skills. There are two main ways to develop data skills within an organisation: strengthening internal talent and outsourcing data analysis.
- Data management – The collection and storage of data, especially personal data, entails serious legal and regulatory obligations. It is therefore vital for all organisations to consider data ownership, privacy and security in their data strategy. If these issues are ignored or not properly addressed, data can turn from a huge asset into a huge liability.
In the business world, information is power, and Big Data is delivering information that we would never have dreamed of collecting or analysing a few years ago. With the huge growth of Big Data and rapidly evolving methods of data analysis, the importance of data in all areas of business will increase. Companies that see data as a strategic asset and develop solid data and analytics strategies will be the ones that succeed in this new data-driven world.
Source: bernadmarr