Data Democratisation: 8 Practical Steps to Empower Your People

Many professionals in the process manufacturing industry equate data democratisation to data access. This article aims to clarify the distinction between these two concepts and explain how you can harness data democratisation to make data work for you and grow your business.

Distinguishing Data Access from Data Democratisation

Data access focuses on enabling people to get data from a source, such as a database or a data warehouse. It is a necessary but insufficient condition for data democratisation.

Data democratisation goes beyond providing access to data. It involves helping everybody in an organisation, irrespective of their technical know-how, to work with data comfortably, feel confident talking about it, and, as a result, make well-informed decisions driven by data.

Why Does Data Democratisation Matter?

Accenture’s “Closing the Data Value Gap” report underscores that most manufacturing firms have yet to harness their data’s potential fully. Only 32% of business executives surveyed said they could create measurable value from data, while just 27% said their data and analytics projects produce actionable insights.

The challenge for organisations in the digital age is not capturing data but rather transforming it into actionable insights that empower employees to enhance operational efficiency and gain a competitive edge. Expanding the pool of individuals with diverse skills and providing easy access to data equips your process manufacturing organisation to pinpoint and capitalise on crucial business insights.

Small groups of technologists and data cannot accomplish this scientists walled off in organisational silos. It requires a much more extensive and diverse approach, including frontline workers: production and logistics operators, maintenance and quality technicians, and their first and second-line managers.

Eight Steps to Achieving Data Democratisation

The ultimate objective is to empower every person to leverage data for decision-making without encountering barriers related to access or comprehension. While this endeavour is ambitious, comprehending the concept and following a systematic guide can significantly simplify the journey. Here’s how to do it:

1. Define Clear Data Objectives

Clearly articulate the role data should play within your manufacturing operations. Reflect on how data can deliver tangible value to your organisation. Consider how operational efficiency can be increased and the waste removed.

Different groups will play distinct roles in creating value from data. Most process manufacturing employees will be users who require rapid access to pertinent data for timely action. Production operators, for instance, need to access data on raw material consumption, energy usage, quality metrics, and environmental variables. On the other hand, maintenance technicians can combine historical maintenance data with production rates and equipment effectiveness (OEE) to optimise maintenance planning and execution.

2. Break Down Data Silos for Enhanced Collaboration

Breaking down data silos within your organisation is pivotal for achieving data democratisation. By fostering collaboration and providing easy access to a centralised data repository, you enable workers to access and share valuable insights more effectively.

3. Invest in Purpose-Built Tools for Industrial Digital Transformation

A legacy of the traditional approach to data usage persists in many organisations: a small group of specialists benefitting from most of the investment in data tools and training, along with universal access to data.

A slow and progressive build-up of tools and work processes is often redundant or provides conflicting data. Wasted time doing manual paper-pushing work can be eradicated.

Investing in tools designed for industrial digital transformation enables more employees to take advantage of data in their work, providing the data and solutions that deliver the right insights. Most users need simple information presented in an easily consumable way that allows them to make better decisions, driving operational efficiency and business value.

4. Experiment and Innovate for Continuous Improvement

Process manufacturing companies should experiment with different digital strategies tailored to their unique contexts. A little experimentation with different digital designs – with varying emphasis on differentiation, collaboration or capturing more value – can yield unexpected, positive benefits in the long term.

An incremental approach involving testing various digital designs can yield unexpected benefits in the long term. Process enterprises can test the solution locally before a global rollout and with key teams by involving them early in development.

5. Provide Support to Solve Issues

Accessible technical support and user-friendly channels for assistance are vital. When workers try to gain experience and find difficulties using a digital tool, the proper response makes a big difference in the buy-in. Having timely support significantly influences the sustainability of data tool usage.

A no-code platform empowers skilled workers in every team to act as citizen developers, allowing them to configure solutions and support their teams directly. This promotes data-driven decision-making, enhances accountability, and boosts engagement.

6. Foster Data Literacy and Make Using Data Routine

Comprehensive data literacy training for all employees, regardless of their technical proficiency, is pivotal. Workers must be able to read, interpret, and communicate data effectively. This will help them feel comfortable working with data and using it to make informed decisions.

Identifying team champions to aid users in resolving challenges fosters continuous improvement in manufacturing. They will serve as references to help users discuss issues and help them find solutions themselves, developing a culture of problem-solving and searching for continuous improvement. Note that this is different from the support team.

Data use should be accessible and routine to avoid overwhelming people. Therefore, discussing with the team the best ways to use data and make it part of the work processes is essential.

7. Promote a Data-Driven Culture for Operational Efficiency

Organisational leaders should actively promote data usage and its value. Once the workers are trained, leaders should encourage the use of data and refer to it. They can set the tone for the organisation by championing data and demonstrating how to improve operational efficiency through data-driven decision-making.

8. Facilitate Cross-Departmental Collaboration for Business Growth

Promoting collaboration across different departments facilitates data democratisation. Sharing data and insights empowers the organisation to make well-informed decisions, creating a continuous improvement culture and business growth.

A process site with separate production, maintenance, logistics and quality teams can easily collaborate and share data to improve overall operations. Some examples of continuous improvement powered by this partnership are:

• Production, maintenance and quality teams could collaborate to identify quality data trends linked to specific equipment or maintenance issues.

• Logistics, production, and maintenance teams could collaborate to optimise production planning and scheduling, reducing production costs and maximising plant usage.

Collaborating saves costs and improves operational efficiency and product quality, helping businesses scale and boost revenue.

Key Takeaways

When discussing digital and data use in the process industry, many picture advanced and high-complexity tools. Indeed, such resources are important for the business. But frontline workers need access to basic, day-to-day technology that helps them better understand their job and improve operational efficiency. They need data and insights in an easily consumable way.

We created Cyzag with agility and collaboration in mind. Our AI-powered platform democratises data access and empowers organisations to increase operational efficiency and sustainability. Would you like to build a democratised organisation and learn how to make data work for you? Schedule your personalised demo.