A data strategy is a roadmap for data usage in an organisation to achieve your short-term and long-term goals and objectives. A modern and comprehensive strategy shouldn’t just define data and its uses, it should also address policies, processes technology and people that support your critical business objectives. A data strategy is only successful when it covers all the requirements of your business and when it takes the human element into account, and not just technical processes for managing and analysing data. An effective data strategy will build a foundation for all your data practices and help you gain a much improved data-driven culture.
Financial Services includes investment banks, insurance companies, stockbrokers and so on. It is a sector that has evolved quite significantly, seeing the digitisation of its data. Management Consultants McKinsey notes that our rapidly accelerating technology, the increasing recognition of the value of data and increasing data literacy, are changing our perception of what it means to be data-driven. By 2025 they expect employees to optimise their work in Financial Services by using data in all aspects of their work. So, what makes an effective data strategy?1. Identify Data Requirements
Your data must address specific business use cases and help add value to your organisation so you should map the kind of data you need and consider:
- Problems with certain IT or technical projects that the data will solve
- Subject matter experts and stakeholders who will process, share and maintain your data
- Different department-specific activities and link them to your data-driven goals
This should enable a clear idea of what data will empower your organisation and your employees and help you solve your existing data challenges.2. Integrate Technology into Data Landscape
Your existing technology has an important role to play in creating a data strategy as it complements and supports the data management framework:
- Assess your data landscape including hardware and software you need for sourcing/collecting, storing, analysing and processing your data
- To get the most from your data you need to integrate the best tools and technology; use data collection tools, data scraping APIs and data storage services
- Implement a scalable data lake platform for diverse operations of data
- Consider both upstream and downstream systems for receiving financial information in a new layout
A robust and effective data strategy should provide recommendations and give actionable insights by applying analytics. Many finance companies still rely on legacy BI tools and traditional ways of analysing data such as Excel reports but by using an intelligent data visualisation platform you will be able to:
- Spot data trends easily
- Enable story-telling by metric-based dashboards
- Provide data granularity which can then be analysed in-depth
- Simplify your data making it easier to understand and interpret
Creating strong governance and reporting models will transform your data from being piecemeal across your company into a secure, actionable and reusable source of truth. It will facilitate:
- Data sharing and analytics practices at an enterprise level
- Ensuring the right people and relevant data owners have access to the right data sets
- Maintaining the data lineage, telling you about the data origins and its transformation journey
- Addressing crucial aspects of a data strategy such as how your organisation ensures data quality, handles issues around security, privacy, accessibility and so on
Selecting the right people as an efficient team is what will drive your data framework:
- You need to map out the roles and responsibilities of the data governance and management team so you need to involve all relevant business groups including the financial planning and analysis (FP&A) team, corporate and local accounting departments and the reporting lead
- Create policies, processes and guiding principles and define governance metrics across the organisation
Now, what next?
Data is driving, transforming, and reshaping the Financial Services industries globally. Wherever you are in your data strategy journey, Catalyst BI’s Enterprise Data Management Health Check can deliver innovative data and AI solutions to help your financial services organisation build a robust data strategy.
Remember, your data strategy will be of no use if the data itself is not stored, secured, and used properly. It is therefore crucial to have a framework in place that ensures your data is well-maintained and ready for use.
With our EDM Health Check, we will combine both technologies and behaviours to measure and manage data and processes, it enables better discovery, transparency and value, scoring a financial organisation’s data management on the following key pillars:
- Data Sourcing and Quality
- Data Integration
- Data Warehouse
- Data Governance