Getting business value from your data: Using data to drive business innovation
Getting business value from your data: Using data to drive business innovation
By Simon Harvey, Head of Data at +OneX
In a previous post I discussed using your internal data to provide real-time insight into your business’s progress towards meeting its business goals, in this post I will explore how you can use data to drive business innovation.
There are three areas I believe that an organisation can drive innovation via data:
• Democratisation of data
• Insightful data
• Artificial intelligence (AI)
Democratisation of data
Sharing data more widely across the organisation can be a spur for innovation. You’ll be amazed by what some of your colleagues will do when empowered with insightful data — whether that’s a salesperson who increases their success in closing deals and upselling to customers, or a team leader who identifies a process bottleneck.
This level of transparent data sharing can improve collaboration across departmental boundaries and catalyse new ways of working. When sharing information with more people across the business, security and data privacy are concerns. However, most modern data environments have fine-grained security features that can be used to restrict access to sensitive data or to anonymise personal information before it is shared.
Insightful data
Getting unexpected insights from data is another way to innovate from your data. Analysing existing data to uncover trends and correlations or detect anomalies are great ways to identify projects or even products from which your organisation can benefit. Simply looking at the data in new ways can highlight insights that one would never have noticed before. These insights may be immediately actionable and deliver real business value in a short period of time with little or no cost.
AI
AI and machine learning (ML) models use data to understand, identify or predict. They can be applied to nearly any prediction or decision that can be made by feeding an algorithm huge amounts of data. A non-exhaustive list of real-world examples includes:
• recommending movies
• identifying the next best action to take
• analysing documents for sensitive information
• predicting fraud
• automating home loan evaluations
• automating the prediction of house prices
• automating insurance premiums
• identifying manufacturing defects
• medical diagnosis
• capacity planning
• inventory planning
• route planning
In the above examples, many organisations have taken their data and built models to make decisions with high levels of precision, in near-real time and without human intervention. This automated decision-making via AI can help an organisation to save money, increase productivity or open up new markets and revenue streams.
Each company should have a strategy to use data to drive innovation to keep ahead of the volatile landscape and competitive pressures of today’s business environment. An organisation that has data and does nothing with it is effectively leaving money on the table. As a trusted data partner, we are there to help organisations get to the most out of their data. Please get in touch to find out how we can provide your organisation with data-driven insights that drive business value.