It’s undeniable that 2020 has forced everyone to learn fast and adopt these learnings promptly.
Throughout the year we’ve continued to speak to data and analytics leaders to capture how their priorities and projects have been evolving and changing.
As we reflect upon the year just gone, here are the top pieces of advice in 7 key areas of data and analytics: organisation, technology and operations, culture, risk and security, innovation, business value and governance.
Whilst there is no one size fits all when it comes to operating models, what is common amongst those that organise themselves successfully is laser-focus on the ability to deliver insights with speed and at scale. Luc Osborne, SVP, Performance and Analytics at a global sports streaming service DAZN explained the organisational structure that helps his company to get the right insights to the right people at the right time.
Resistance to change is often cited as the key roadblock in creating a data-centric culture. However, adopting a new mindset and behaviours is key to becoming truly data-driven. Bill Hoffman in his recent Data Leaders Masterclass summarised the key steps to consider when looking to improving your organisation’s culture.
- Identify the key elements of a data-driven culture that you will focus your efforts on.
- Identify the key personal and structural biases that might get in your way.
- Consider the importance of the Forward-Deployed-Insights (FDI) professional to translate data for you.
- Look at the talent you have in your business.
- Assess how engaged your employees are and how this can be improved.
It’s challenging, however, to embed data at the very core of the business if your workforce lacks an understanding of what data means. This year we have seen more people starting to shift their focus towards data literacy. A former Gartner analyst Valerie Logan explained the right time to start working on it.
Whether it’s creating efficiencies or building new products, becoming more innovative with data can provide a competitive advantage business are looking for. Daryl D’Cruz, Former Head of Data Innovation at Samsung explained that the data-driven culture is a critical foundation needed in order to allow people to experiment, test, and create.
But as businesses embark on the journey to uncover new value with data science, they must not fall into the trap of quick returns: “Data science is such a complex arena that for it to be impactful it has to be a consistent conversation”, said Daryl.
To boost the effectiveness of data science, leaders have to resist asking all the questions and instead focus on asking the right questions. Take time to get to the heart of the problem, really understand the business value you are trying to create, and build innovative solutions from there.
As awareness of the power of data is growing, more business leaders turn to their data teams to understand how powerful it can be. We are seeing more companies trying to put monetary value on their data – yet, data valuation methodologies are not easy to implement. A good starting point can be this outline produced by PwC.
Almost as important as the business value itself is your ability to communicate it. Scott Taylor shared the concrete practical steps data professionals can take to get their message across by creating a better narrative.
Technology and operations
2020 has demonstrated how businesses must be prepared to respond to change and transform themselves quickly. Didier Mamma, VP, Data Value Creation at Decathlon argues that our ability to predict the future is still very low, but once companies understand that, they can organise themselves to become more agile, iterate and recalibrate themselves quickly. In the recent interview, Didier explains how to future-proof your processes.
Risk and security
“You should have your CISO on fast-dial”, says legal counsel Jane Hunt asked about her advice for CDOs. At the time she explained the implications of the EU ruling Data Privacy Shield invalid.
As one of our event attendees put it earlier this year: “Making data governance a business matter – not only IT – is a major success factor”. Bill Hoffman went into more details on why the best companies typically follow a 3-phase approach to data governance excellence:
Phase 1 sees them use the insights team as a store, with positive ROI generated in the first year and a handful of clear use cases showcasing positive ROI.
Phase 2 sees the insights team owning the single version of the truth across the business. They’re capable of showing clear improvements on customer experience scores and the customer value proposition.
Phase 3 sees insights move out of the central team and become a toolkit for deployment across the business. The work is capable of generating over $5 million in incremental revenue and has clear executive buy-in.
However, as we look towards the future, Data Leaders believe the data governance will soon be more automated.