How corporates can make the most of their data and how to understand the social value of data
Strategic Considerations
At Forecast we define the data journey as “crawl, walk, run”. Companies are often trying to run too far ahead with their data when they should first aim to get the right data infrastructures in place. The lack of a unified data strategy is one of the driving reasons for businesses failing to make the best use of their data, especially in situations where they can take advantage of more advanced use cases such as Machine Learning (ML) and Artificial Intelligence (AI). These need a different operating model within the organisation that ensures that teams collaborate rather than working in silos.
Another blocker for making the best use of their data is when different areas of the business have divergent technical strategies. An example of this is where the data engineering team of an organisation are focused on a micro services approach and trying to break up the data, where the CFO is trying to collect and consolidate it. One option to implement in order to solve this particular problem is defined as “the data mesh”, which focuses on leaving the data in place and connecting it up.
Data Quality
As part of how we operate at Forecast we begin with a discovery process to understand what our clients are trying to achieve with their data alongside any challenges and opportunities, systematically walking through this framework to prioritise the higher impact things first. In keeping with the pitfall highlighted earlier, the availability of good data does not match the stage that the business believes to be on the data maturity curve. Here we tend to encounter obstacles such as data quality, mismatched data and data lineage. A benefit of working with Forecast is that we work across the data spectrum, and involved as early as possible to help identify and resolve these issue.
Security
One of the most significant challenges that companies face is around the security of their data. Cyber security has been identified as one of the biggest threats in the global economy, and as a result of that cyber security will become a focus point of foreign policy. As the volume and diversity of data grows and the data industry grows with it, there will be a more attentive focus on regulations that focus on data and it will have a significant impact in the way companies operate and serve their customers.
Regulation & Ethics
As the amount of data continues to grow exponentially, data ethics becomes more salient and relevant to businesses due to the impact it has on individuals. From a legislative perspective the data privacy act and GDPR recognise this, but it is unlikely that legislation will be able to keep up with this pace. With that, companies will need to use all the tools at their disposal to ensure that the challenges around data ethics are addressed. As an example, we have noticed that in the banking sector data sovereignty represents a significant issue in terms of where customer data is held. Many banks in the UK are inclined in to put data in European data centres or cloud data centres based in Europe. This creates concerns around data residency and implications of where the data is processed. Our framework takes issues such as these into account, and looks with a detailed lens over points such as:
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What is the nature of the data that is being processed or used?
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How much data is there?
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What do you actually want to do with the data?
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Can individuals be personally identifiable as a result of processing the data in a particular way?
At Forecast we are equipped to help deal with these challenges. Our team are trained to deal and process data in a particular way. The principles and policies that we have in place guide and advise our clients on best practices to ensure data safety.
We know many organisations are struggling with this, if you would like to discuss with us how to move along the data curve, please do not hesitate to get in touch.
