I recently hosted our client summit, “Smarter data. Smarter decisions.” This annual event is an opportunity for our customers to hear from industry experts, share ideas with their peers and find out how Experian solutions can support their data quality ambitions. On the day we heard from Tom Pringle, Practice Leader at Ovum, who gave us his views on how data management can improve business analytics and customer Michael Wolman, Head of Analytics and Insight at Win Technologies, who explored how his organisation has embraced data analytics to drive decision making and the data management journey that sits behind his success.
Unfortunately not all our customers could make it on the day, so if you were one of them I’ve collated a brief summary of some key themes I found most interesting.
1. Data means big opportunity
Data is now undeniably accepted as the driving force behind organisations, helping to redefine and build new business models. With this comes positive change; CDOs that were originally focussed on regulation and compliance are now starting to take a more creative view about how data can start to “earn its keep”. At board level there’s huge appetite to make well informed decisions based on real insight over and above ‘hunches’ and that’s putting data management on the agenda and improving investment.
With this enthusiasm however comes the risk of an assumption that data will solve everything. Having the right data can empower and guide business strategy but the wrong data can have the opposite effect and be detrimental to progress.
2. Data analytics and data management aren’t mutually exclusive
Analytics is often seen as the shining beacon, delivering the insight that drives business. Whats critical however, is that the data management and quality that fuels it is right or the whole thing falls down. Poor quality data will only ever produce inaccurate analysis, which means any organisation looking to drive its analytics function should ensure that data management is also brought to the table as part of that.
Making this a reality requires:
- A clear definition of who builds and maintains the quality of your data vs. those responsible for driving the insight from it.
- Alignment of the processes and agreed metrics across the business to ensure everyone is “singing from the same hymn sheet”.
3. Self-Service is increasingly commonplace for data driven organisations
Putting data into the hands of the users who need it is a recurring theme. Self-service opens up a whole new opportunity for them to uncover opportunities and that empowerment gives genuine business engagement to use data more creatively. Despite the value this can provide, there are a number of important considerations:
- Quality – those accessing and using the data will only be able to get valuable insight from data that is up to date and accurate
- Metrics and definitions – a data dictionary is an invaluable asset to give everyone access to a consistent record of what every term means so they can analyse data more efficiently and consistently.
- Training – regular training is one of the most important elements of self-service in order to ensure best practice and consistency with the metrics across the board.
4. It’s your people that make it happen
As data becomes more high profile you may find many are enthusiastic about the possibilities but have less interest in taking responsibility for it. It’s here that securing the right sponsorship is vital. Having senior level buy in allows for the creation of the right roles and mix of skills in the business, something which can often be a challenge. With a team and roles in place it then becomes easier to build a data culture that embeds its importance into everyone’s roles. This takes time, but having data represented at every table across the organisation helps to visibly demonstrate how data drives successful decision making at every level from marketing, to operations, right up to strategic considerations.
5. The right technology is the final piece of the jigsaw
We heard numerous references to technology being an enabler and whilst in isolation it won’t solve all your problems, when coupled with the right people, processes and culture it becomes a critical success factor. Tools such as Experian Pandora
are perfectly suited to organisations looking to move up the data maturity curve
, delivering not just on data quality requirements but also providing quick time to value, interactive graphs and charts to analyse data and an intuitive user interface that’s easily accessible to business users.
It was encouraging to hear our speakers discuss themes that resonate so closely with the challenges that we see customers face every day. During the second part of the day we moved into a series of more focussed breakout sessions designed to drive discussion amongst customers around maturity, getting buy in and creating a data driven culture. Look out for a series of blogs where we’ll delve into each in more depth.