Successful companies have always made decisions based on data. The more you know about your own organisation and about your competitors, the greater advantage you have. 

Today, data is one of the largest and most important assets in your business. 

New ways to source and leverage data are leading to far more sophisticated data-driven decision making. The data is more granular and the insights they can generate are more powerful, leading to better day to day and strategic decisions.

Organisations looking to move towards becoming data driven, need a plan that will allow them to progress along the digital transformation path to where data is seen as a genuine corporate asset. And developing a data strategy is the first essential step on that journey. 

The Data Plan

Having a company-wide data strategy sounds impressive, but what exactly is it and what problems will it solve for your business? A data strategy incorporates all the architecture, services, and processes for all aspects of sourcing and using data. This includes data:

• Acquisition
• Integration
• Storage
• Security
• Management
• Monitoring
• Analytics
• Operationalisation 

A data strategy is your framework and roadmap towards complete digital transformation. It should include the company’s vision and the practical steps required to achieve it. It can help you make better use of data analytics tools and capabilities to make your processes more efficient, your staff more effective in their roles, and ultimately increase the productivity of the business to make it more profitable.

All elements of the data strategy should be agile and created in a way that they can provide ongoing, iterative value to the organisation. This means the strategy can evolve over time and grow as your organisation grows. It should be created in a way that allows feedback or recommendations over time from all levels of the business, not just from senior management. 

If you can’t measure it, it hasn’t happened. So, the data strategy also needs to include clearly defined success criteria and performance indicators to evaluate progress and refocus future data initiatives. 

It’s also worth detailing what a data strategy isn’t. It’s not a comprehensive solution that covers all data use cases or specific technical issues. Nor is it just a high-level overview only for executives. It needs to be a live plan that outlines how data is to be used at all levels and how it will help you achieve your organisation’s goals. As new technologies emerge or organisational goals change, so should your data strategy. 

The Data Strategy Recipe

The following provides a list of all the components your data strategy should have so that it can be implemented in an effective way that drives value for your staff and for the business:

• Glossary - a breakdown of all data terms and topics so that everyone is on the same page with how data is named and used.
• Vision - a clear explanation of the data strategy’s goals and how they help the company meet its broader business goals. 
• Principles - outlines the standards and processes that the entire organisation adheres to in relation to data use. These should be business focused principles but also be aligned with the technical data principles and functions. 
• Current state - provides a snapshot of how the organisation’s data operations function at the time the data strategy is first created. This provides a baseline for evaluating capabilities and the maturity of the data model that can continue to be built on and developed. 
• Governance - provides a breakdown of the standards the business must adhere to in its use of data. This can include regulatory compliance requirements as well as voluntarily introduced standards to improve data security and privacy. The governance model should outline the procedures and methods for managing the data and solution life cycles, including operational and support-control handoffs. It should also detail how change management is handled within the organisation so that as the technologies or data management processes evolve, there is a clear method by which these iterations are implemented. 
• Data management - the standards and methodologies for managing data elements including data topics and metadata. This should also cover the data stewardship processes in place such as curation and audit processes to ensure data is properly stored and used only by approved staff. 
• Architecture - this is a reference architecture that both accounts for the existing standards and implementations as well as allowing for new standards and innovations to be introduced to support the business as it evolves and scales. 

Implementation

A good data strategy can help crystallise the enterprise’s data utilization goals as well as help it achieve them. Once a data strategy has been developed, now it's a matter of going out and implementing it. Remember that the data strategy is both a short term and long term plan. So continue to use its framework for day to day data management as well as to update it as new data- centric capabilities or analytics products, tools, and services are created and used. 

If you’d like to find out more about how to make the data strategy become a core element of your company’s digital transformation, talk to the experts at FinXL.