In the run-up to Big Data LDN 2018 I got to thinking about this year’s theme “From the Fourth Industrial Revolution to data utopia”. Most large enterprises I’ve been working with this year are transforming digitally, striving to reach that utopia.

In reaching that destination, I believe nothing is more fundamental than cultivating a healthy enterprise data democracy where:

EMPLOYEES at ALL LEVELS are EMPOWERED TO ACT on RELIABLE DATA that they can EASILY ACCESS, ON-DEMAND to have a POSITIVE IMPACT on the BUSINESS.

To many enterprise leaders, this definition may seem a bit too utopian to be achievable. However, over in the consumer world, this model already flourishes. People use tools like Google, CityMapper and Amazon to make efficient, data-driven decisions every day. The widespread use of these tools in the consumer world is making people more data-literate generally.

So what’s stopping data democracy from thriving in the enterprise world? These are some of the classic barriers:

Fear of anarchy - Managers often fear that data transparency and empowerment will lead to anarchy and chaos. Some managers also fear that sharing power means losing power.

Data access and speed - The value of data diminishes over time. If it takes time for end-users to access the right data for decision-making, employees working at the coalface won’t be able to solve problems when they arise.

Mistrust in data reliability - When data is unreliable, it leads to various problems. People who fear making mistakes often err on the side of caution. For example, a planner might decide to hold excessive ‘safety stock’ in inventory as insurance, leading to costly obsolescence and waste. Others might use poor data reliability as an excuse to discredit any data that they don’t like. However the most common reaction to low or inconsistent data reliability is indifference. People will simply ignore the system and act on their gut, or ‘rogue’ datasets gathered informally.

How do enterprises that urgently need to transform overcome these barriers?

1. Attack corporate inertia - Much of the fear of anarchy lies in corporate inertia. When managers don’t challenge established processes and policies, including access to data, they limit employees’ ability to excel in their roles. Managers must be brave and critically evaluate their investment, prioritisation and decision making processes. Yes, data protection and security are paramount, but modern analytics tools are engineered to manage these issues.
2. Make the argument for less anarchy - When employees aren’t given access to data, they find a way to get it through informal channels. They store it in spreadsheets, on laptops and devices, and often use this data out of date, and out of context. That’s a particularly dangerous form of enterprise anarchy that leads to unwelcome surprises. I’m seeing first-hand through my work with large enterprises that easy, non-bureaucratic access to data actually creates more order and improves outcomes. When empowered employees are given reliable data, they act responsibly, evaluate decisions more carefully and make better decisions.
3. Accelerate the “last mile” - There are two game-changing technologies transforming the so-called “last mile” of analytics: search and AI. Search-driven interfaces give people data answers with the same ease and speed as Amazon or Google. They give quick answers to simple natural language questions in near real-time to make smart day-to-day decisions. This continuous feedback and interactivity reinforces people’s use of analytics and helps to cultivate a data-driven, data-literate culture.When people don’t know what to ask in the first place, smart AI-driven systems can assist people by identifying trends and outliers in data sets and propose searches. These proposed searches can even be tailored to individual preferences and roles.
4. Build a trusted data environment - Educating users and stakeholders on how data is sourced, how it is refreshed and how roles and access privileges are setup all contribute to building trust. New BI tools also make it much easier for end users to understand their data lineage. Simple data labels and visuals of data sources, joins, roles, user privileges all support this. Users also have greater confidence and trust when decisions are supported by large and varied data sets whose provenance they can trace.

Achieving data utopia is not about giving people the ability to generate more reports to satisfy their bosses. It’s about empowering the entire workforce with right skills and tools, to make decisions that help them to succeed personally and contribute to reaching business goals.

To find out more about how you can achieve ‘data utopia’ please visit ThoughtSpot at Big Data LDN in stand 115.

Article by Amir Qureshi, Regional Customer Success Director, EMEA at ThoughtSpot