Think of data as the new oil.
When it leaks, it’s as bad as the BP spill; you need only remember the data breaches that affected everything from credit cards and government agencies to data breach protection companies. Meanwhile, data is also a valuable resource that people readily mine and monetise, leading to major revenue for businesses.
As data’s power grows, so does the movement to increase accessibility—also known as data democratisation.
Democracy, meet data
Let’s start at the genesis. As buying experiences become more omnichannel, customers widely indicate their wants and needs online. While some companies use those indicators to their competitive advantage, others aren’t so lucky.
Often, this isn’t due to insufficient data, but rather insufficient resources that can clean, process, manage, aggregate and analyse it. However, hiring a talented data scientist is only the first step. The struggle to retain that person, when data scientists switch jobs on average every 2.6 years, is eternal.
So what happens when data is the new liquid gold: more valuable than ever, but also harder and more important to mine? This is when democratisation becomes so important.
Public data is moving towards democratisation, what about private data?
Democratisation already has inroads in the public space. Think of how governments both at home and abroad collect demographic data on populations. UNICEF offers up datasets on women and children, the World Health Organisation contextualises hunger and disease, and NASA keeps stacks of satellite imagery about the entire globe, available to everyone.
It’s easy to see how these datasets make the case for democratisation.
However, the Big Data that runs companies brings with it an entirely new set of considerations.
The explosion of internal organisational data comes from everywhere: manufacturing, quality assurance, supply chain, personnel. Add on even more external touchpoints like customer service data, purchase history, web browsing, app usage, in-store visits, email reads, and offers used. There’s a major benefit to leveraging the data you have that your competitors don’t. Take Amazon, a noted leader in using data for differentiation, utilising data to personalise your shopping experience, making purchasing easier (think one-click ordering or tiered shipping models) and the platform the go-to ecommerce platform.
Today’s data analysis efforts can be massive and siloed. What if you only used Salesforce’s data in isolation, and had to keep your Google Analytics data separate from that, while Zendesk data could only stay within the bounds of its platform? Doing deep analysis on this siloed data can be helpful, but combining these sources is crucial to finding the real insights that help drive ROI across the business. Once organisations empower internal teams with access to usable data, those that best combine data will be positioned to best leverage data for anything from cross-channel identification of customers to full-fledged marketing performance and ROI analyses. Take STX Entertainment which used location-based intelligence and demographic data to market its latest movie or Herradura tequila, which worked with Foursquare to encourage consumers to go to locales where the liquor was sold.
Getting data in front of people spurs grass-roots creativity
A recent McKinsey report advised that when it comes to data democratisation: “Get data in front of people and they get excited. But building cool experiments or imposing tools top-down doesn’t cut it. To create a competitive advantage, stimulate demand for data from the grass roots.”
Here’s just one small example of democratised data in an organisation: If a tool can take the weight off of data scientists by allowing other team members to perform analyses, it ensures that the entire organisation is making more data-driven decisions.
One new category of tools helps redistribute an organisation’s customer data by pulling it into one database and providing tools to allow for analytics across different types. Customer Data Platforms (CDPs) help create a “golden record” for each customer--a single, unified place to collect behavioural and demographic data from a variety of platforms. These standardised records reduce redundancy and streamline every business process that makes use of customer data.
Sales and marketing have the highest potential
In the same report, McKinsey named sales and marketing as the top departments that can benefit from data democratisation.
For example, consider using a strong source audience of your best local customers to create a broader national lookalike audience (with the help of machine learning) for use in digital campaigns. Or, consider combining shopping data and location-based data to truly customise outreach to a specific audience in a proximity-based marketing campaign. More precise investment drives more qualified leads into the funnel and strengthens the sales team’s belief that any marketing lead could turn into a sales lead. Any of these projects could be a strong proof of concept for internal buy-in on data democratisation.
Prove the concept, provide the solution
So, how exactly can you drive value through data democratisation?
- Call it out as a priority. This means investing in systems, tools and processes where everyone has access to data and data-driven decisions are rewarded.
- Nominate a leader to head up the effort. Without a face to head up data, often even the best plans can languish. Ensure there’s a person who is holding the entire team accountable.
- Create a good—and phased—plan. Often with big change, teams want to do everything all at once. But there’s no need to boil the ocean. Instead, start with a phased approach via a proof of concept like the ones mentioned above.
This rollout, starting with a proof of concept, helps for buy-in internally you can seamlessly move from proof of concept to full implementation with the right platforms.
Sure, data democratisation is good and proof of concept is great. But proof of value? That’s what will get the approach to stick.
Tom Treanor, global head of marketing, Arm Treasure Data