In this episode Jason talks to Carlos Soares, the Chief Data and Analytics Officer at Analytics Worx (formerly the Chief of Data at Diageo and Senior Director of Analytics at Nike, Vodafone and Liberty). They discuss the importance of delivering value-based data, and why you need to create a safe space for your data team to innovate and improve constantly.
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If you are a CDO, or data leader setting the data strategy at your organisation, find out more about the CDO Hub.
Over the past few years, the role of data leadership has changed drastically from keeping track of inventory to coming up with huge data solutions that span across multiple departments. This is proof that in such a fast paced field as data you need to be willing to constantly learn, transform and expand – otherwise you’ll be left behind.
[00:43] Carlos explains his various data leadership positions at some of the biggest brands in the world
[03:20] What value-charged analytics means and earning credibility
[08:50] How the data basics in a company can actually be the most transformational
[10:30] Why it is so important to know the company values and bring employees on board
[14:00] How to align the day-to-day operational strategy with the company’s long terms goals when creating a data strategy
[21:20] Finding the balance in data leadership roles between advocacy, consulting and implementing
[26:10] How to ensure you have a team that delivers
[30:40] Creating a community when you are leading a data team
[33:29] The most interesting piece of data information Carlos has ever delivered to a company
Keep track of the top key performance indicators when creating your data and analytics strategy. Don’t rush ahead creating fancy data strategy until you can demonstrate that you have an understanding of what the business needs and can execute appropriately.
Always strive to provide value and use every opportunity to demonstrate that you and your data team are here to support the business and the big vision without losing sight of the smaller details.
It’s not always easy to create a team that is capable of delivering what you promise.
When it comes to larger companies with bigger data teams it is important to create a place where they can keep innovating and improving.
There are three core factors in creating an environment where your team can stretch their abilities and learn new things
Sit down with your staff, get practical experience of the day to day operations of the company and get as much knowledge as you can before coming up with data solutions. Allowing employees to open up about problems can help you facilitate necessary resources and provide extra help to those that need it.
Don’t be afraid to delve deeper into why leadership requests certain data. Delving deeper into why someone may want a sales report can uncover other problems with market research, inventory and demand – all things which data can help solve.
Data analytics is a team sport: everyone needs to be on board when it comes to a company’s data strategy. Oftentimes, leaders are unsure how to start integrating data knowledge into their company. Do they start by educating the leaders? Do they upskill their data expert?
The solution to this dilemma is by creating a pincer approach where both sets of company employees are educated simultaneously. The education at different levels of a company will always look different: what leadership needs to know about data will inevitably be different than what someone in the marketing team needs to know.
Creating a pincer approach to data education requires leadership to acquire some working knowledge of data. It also requires the boots-on-the ground staff to discuss problems that can be solved with data, integrating the importance of data into the company culture itself.
When data is integrated into the company in this way, it helps to smooth the flow of information between the ground staff who can identify problems, through to the data team who formulates strategies and the decision-making leadership team who give the sign-off.
Always align the business goals with the day to day objectives of the business when planning a data strategy. Doing this can save a lot of time and money by addressing core problems without wasting resources on projects that don’t align to the business.