For many, the term business intelligence conjures up images of monolithic applications and staid reports, raising the question of what value it generates for businesses facing complex analytical challenges. However, given the expertise developed and extensive historical investments in business intelligence, companies would be unwise to get rid of their existing systems. Instead, how can they evolve their capabilities to tackle opportunities head-on?
Ahead of his presentation at Business Analytics Tech Fest, Ryan den Rooijen, Global Director of Data Services at Dyson shares insights into what a modern analytics journey looks like, as well as practical principles that can help companies successfully navigate this path.
How is the world of BI, insights and analytics changing?
What companies are realising is that being able to use data to build better products, and to make better decisions, has become one of the primary drivers of their business’ value. This is coupled with technical and cultural changes that enable businesses to democratise access to data, and to empower a much broader set of users across their organisations. Finally, this also allows people to consider how data is leveraged. For example, sales records that only served financial reporting needs in the past can now be used for predictive inventory management.
What challenges do these changes present to businesses facing complex analytical challenges, that have invested in traditional BI initiatives?
Change is always difficult, but doubly so if it follows significant investment. Therefore, it is key to stress that the aim is not to throw out the baby with the bathwater. Instead, how can an organisation augment the work that was done previously, with new capabilities, such as introducing the ability to work with streaming data or machine learning? This involves reframing the culture around BI from reporting to recommendations: moving from reductive to expansive. Finally, business areas should be encouraged to invest properly in governing their data and making it available to the organisation. While breaking down silos can take time, particularly as companies look to leverage AI, it is critical to “stock the pantry” with compliant, high quality data.
What are the real-life examples and success stories at Dyson?
Dyson is growing rapidly, which provides us with many great opportunities for data analytics. Whether it is improving the way we forecast sales, or building our insight into customer support, we use advanced analytics in many parts of the organisation. After all, in any process where humans are making decisions based on a certain volume of data, there is an opportunity to improve that process using AI. The nature of BI is evolving well, allowing us to work increasingly with real-time data instead of dealing with reports that run on a daily or weekly basis. What these projects all have in common is their clear business value and impact on the organisation.
Top Five Tips for Analytics Success
- As with any journey, start with the destination in mind. Where are you trying to go? What is the minimum you wish to achieve? What compromises can you make along the way?
- Break out of your rivers of thinking. Don’t settle for the status quo. Analytics has transformative power, so use it! Where can you add the most value quickly?
- Consider the team and the resources at your disposal. Where should you start? What is feasible given inevitable constraints? How do you develop your capabilities over time?
- Modern BI technologies offer great speed, agility, and interoperability. Break down traditional technology silos and keep an open mind in regards to what solutions you decide to use.
- Weave governance and security principles into your plan from the beginning, and you will not be faced with unpleasant surprises down the road. Use these as differentiators.
About the Author
Ryan den Rooijen is Global Director of Data Services at Dyson. Ryan leads Dyson’s Global Data Services organisation, who work on transforming the company’s analytical capabilities. From manufacturing to marketing, their work spans the breadth of Dyson. Previously, Ryan spent four and a half years at Google, where he led the development of the global sales analyst curriculum. Most of his work involves the practical application of big data analytics – impact, not buzzwords. DataIQ repeatedly named him one of the most influential people in data-driven business. Ryan completed an MSc in Social Science of the Internet at the University of Oxford. In his spare time, he enjoys running, reading, and traveling.