Your data strategy and action plan are critical in helping you maximise value across your organisation.
CFOs and FP&A teams are under pressure to provide their business with fast, accurate and actionable insights. However, most businesses do not have the organisational structures, and data frameworks in place to support this transition.
Harnessing your data is the first step in creating a robust action plan and will set your finance team up for success. Review our 5 questions to complete your data strategy and go from steward to strategist.
You must walk before you can run.
Advanced predictive analytics and AI are ‘the way of the future’ but, before you can reap their benefits, focus on your foundations. Adopt an agile mindset and stay flexible when developing your strategy. We like to say, “think big, start small.”
Setting high expectations for data consistency is necessary and there are 5 key questions that your data strategy must answer:
1. What data do you want to obtain from enterprise systems?
2. What processes will you use to obtain that data?
3. What level of data transformation do you require?
4. Who within your organisation can help you make the change happen?
5. What technology do you need to bridge the gap?
Let us review these questions in more detail:
1. What data do you want to obtain from your enterprise systems?
Not all data is useful. Be ruthless in what data you collect and store.
The key is to align your data strategy to your company’s strategic objectives. Review your company’s KPIs and goals, then, re-engineer the data that is required to measure the success of these indicators.
By getting clear on your company’s goals, you can begin generating real value for stakeholders. Focus your efforts on providing them access to data that will allow them to discover insights.
2. What processes will you use to obtain that data?
How you collect and govern data is critical to your strategy. Develop an inventory of all data sources and applications and establish who will be responsible for each. Ownership over data sources will help people to become more accountable for the delivery of accurate data.
The next step is to make the collection of that data more efficient. This is where automation can help to reduce manual task time, as well as increase speed and accuracy. There is a plethora of tools available in the market for Master Data Management (MDM). For example, batch/parallel processing which can be used for large volumes of data, as well as platforms that act as a ‘search engine’ for your data, making it easier to access valuable data.
Spend time on high value activities, such as data integration. Remove data silos and ensure there is no duplications of effort or data sources. The goal here is to keep your stakeholders front of mind, and provide end-users with a unified view of enterprise data.
3. What level of data transformation do you require?
Data transformation will help make your data insightful. In this instance, set rules and expectations that ensure all data is transformed into a common, usable format.
Modern data warehouse technologies, such as Snowflake, leverage the power of cloud computing to separate the physical tables from the compute power. In doing so, end users can load raw data and then perform ELT processes to transform the data. The benefit of this method is that you maintain all available data for future requirements.
4. Who within your organisation can help you make the change happen?
Some believe one of the hardest parts of implementing a robust data strategy is managing the people. Early on in your data strategy, identify ‘Change Evangelists’ – the people within your organisation that will lead and enable learning and accountability.
Evangelists help you build the business case for change and ensure new processes are followed.
5. What technology do you need to bridge the gap?
Lastly, a big piece of the puzzle relates to the technology you employ. There are so many solutions on the market, that it can be hard to distinguish tools that allow for true integrated analytics, planning, and forecasting.
At this stage, many people seek the assistance of specialists outside of the business who can provide an objective overview of tools available. Choose a ‘future-proof’ solution that allows you to get your data foundations right. Similarly, look for advanced features such as AI technology that you may use in the future.
Remember, you may come up against resistance to change when it comes to implementing new and unfamiliar technologies and processes. However, it is important to stress internally that technology is an enabler of empowered decisions. Once you implement your data strategy, you can begin measuring the value you bring to your organisation and its people.
If you find it difficult to start your data management strategy and want to impart greater impact and value on your organisation, contact us at Minerva Partners?
We are a Management Consultancy laser focussed on business transformation. We assist CFOs every day to improve their data management, budgeting, forecasting, and planning, allowing them more time to focus on business growth and strategy.
