Competing in a data-driven world

To stay competitive and effectively manage complex systems and assets, industrial companies are turning to data-driven solutions to augment their employees in their day to day operations. These techniques are emerging as vital tools for providing analytics and management support in areas such as asset reliability, process optimization, risk management, supply chain management, or other industry-specific data interpretation and analysis.

The new leaders invest heavily in data platforms, data sources, and analytical skills to extract all of the insights they need to move the business forward, whether it’s for energy efficiency and emissions control, fleet benchmarking, costs optimisation or predictive maintenance. By enabling your organisation to leverage the vast amounts of data you collect from systems and sensors, analytics can uncover critical insights that both speed up and improve the quality of management decisions. And as data-driven strategies take hold, they will become an increasingly important point of competitive differentiation.

Aquantico’s data strategy and consulting services can help you build a functional data strategy, that leverages Data Analytics, IoT, Cloud & AI to derive value from data through six value modes:

  • Enhanced processes
  • Improved asset performance
  • Improved competitive position
  • Building data into products and services
  • Augmented human capabilities
  • Improved risk management

We adopt Design-Thinking centred approach, to determine your business needs, your strengths, pain points and then develop a roadmap to prioritize the ways you can apply it to your business and prepare your organisation for success.

Factors driving the growth of AI across the industrial value chain

Data and analytics have altered the dynamics in many industries, and change will intensify as machine learning and deep learning develop capabilities to think, problem-solve, and understand language. The potential uses of these technologies are remarkably broad, even for sectors that have been slow to digitize.

Underpinning this progress has been the combinatorial power of open source technologies and how organisations can tackle business problems with a whole new mindset.

Three factors are shifting the speed, scale, and economics of innovation faster than ever before: increasing data volumes, computing power and decreasing costs of computing.


IOT & Sensor technology has made data acquisition seamless and cost effective. As a result, everyday products to industrial assets are increasingly designed with built-in sensor technology and intelligent software solutions. This makes it easier to turns data into insights, predictions and recommendations.

Cloud storage

Cloud systems make data much more available, enabling organisations to share data more effectively both internally and externally with OEM vendors and partners. Over the last decade, data storage costs have dropped by more than 95%.

Computing power

Data processing capability and artificial intelligence applications are increasing at an exponential rate and cheaper to deploy. This has accelerated growth of machine learning and artificial intelligence across every industry, allowing organisations to analyse vast amounts of data more effectively.

The journey to becoming data-driven

Fundamentally, emerging technologies now can empower industrial organisations to leverage data themselves, putting the benefits of Artificial intelligence (AI), blockchain, cloud and IOT in the hands of industrial operators by simplifying the process of building, training, and scaling industrial AI driven applications in their day-to-day operations.

Blockchain for example can enable more transparent, cheaper and accurate end-to-end tracking of transactions in the supply chain.
IoT, sensors and edge computing devices can dramatically enhance automation, data collection, and analytics, in addition to optimizing workflows and processes. Cloud-based applications can process data into useful intelligence and transmit it to machines on the ground, enabling mobile, real-time response.

Finally, AI based industrial data platforms improve processes by detecting patterns and turning machine data into insights, predictions and recommendations.

To create an effective digital strategy, we bring together stakeholders, subject matter experts and our technology partners to design a solution plan that is both people-centric and digitally-powered, aligning management, employees, customers around a shared purpose and vision.


Making sure your business and leadership are agile and ready to capitalize on new insights gained through intuitive data analytics platforms.


Improving the efficiency of your decision-making through the integration of relevant, reliable data and insights with more efficient business processes.


Using innovative technology to automate and expedite data analytics, data management, and essential business operations while mitigating risks.


Managing your data as an asset and applying powerful data analytics to ensure that all key decisions are based on the best and most up-to-date information.

Business Applications

Real time performance monitoring

Automate the collection and analysis of sensor data to monitor and benchmark the performance of critical assets. Effectively map the assets current state and understand how input conditions, e.g. temperature, and vibration, relate in the asset operational performance.

Real time performance monitoring

Predictive maintenance analytics

Reduce O&M costs using advanced analytics to implement predictive maintenance programs, optimize asset health, and identify underperforming processes. Leverage machine learning to detect anomalous asset behaviour and predict potential failure events

Predictive maintenance analytics

Prescriptive Analytics recommendation

Use natural language processing solutions to assist maintenance technicians prescribe faster corrective actions by mining and analysing years’ worth of company unstructured data, such as job reports, maintenance logs and OEM equipment manuals.

Prescriptive Analytics recommendation

Supply chain management optimisation

Streamline your supply chain and logistics operations with blockchain technology. Moving away from paper-based processes towards digitally verifiable and legally enforceable documentation means cheaper, efficient shipping operations and the reduction of fraud.

Supply chain management optimisation

Commodities End-to-End Traceability

Deploy blockchain business network to securely manage the transactions and documentations in a transparent manner amongst all parties involved throughout the entire production lifecycle of agricultural and mineral products, ensuring traceability, trust, stewardship and compliance.

Commodities End-to-End Traceability

Corporate carbon tracking and trading

Digitally certify the emissions footprint of energy usage of any asset on an immutable ledger using IoT devices and blockchain technology. Use smart contracts to automate CO2 impact calculations and tokenize the savings for use in a Carbon Credits Marketplace.

Corporate carbon tracking and trading

Data strategy roadmap

Creating an effective data strategy requires assessing your specific business challenges, matching those challenges with relevant data and resources, and establishing processes that grow your capabilities and empower your employees. 


Define your objectives

We work with you to define the main objectives of your data program, involving the key stakeholders to frame the challenges to be solved and outline the target end-state for the short and medium-term. It’s about defining the guiding vision of how is data going to support the business, and establish clear and measurable milestones to inspire and mobilise the organisation.


Assess resources and identify gaps

Next, we determine what data we are going to need, assess current technology assets and think through the processes in place for collecting, processing, and distributing the data; mapping the stakeholders for each these activities. We’ll help you select a data management solution for your business that is modular, flexible, open source and validated by a strong community of active users.


Identify and prioritize use cases

Select a range of use cases that fit the business objectives and that achieve buy-in from key departments in the organisation. We rank them along three dimensions: Cost, Return on Investment, and Actionability to create a roadmap with a sequence of projects. We start with simple, low-investment projects to provide quick returns to win buy-in across your organisation.


Set up robust data governance

We assist with the implementation of strong data governance, with clear accountability for data quality, security, and privacy, and help deploy permissioned self-service tools to ease data access across the organisation. This is a great step in fostering a real cultural change by turning data analytics into a day-to-day contributor to the business rather than a perceived business function.


Create a plan that scales

We balance potentially longer-term initiatives with shorter time-frame projects and deliver components often and incrementally with higher value, presenting data insights in a format that anyone can understand. Along the way we pivot the organisation and culture with new capabilities, engage and empower employees, and train people to leverage the new digital capabilities.

Data is no longer a by-product of business processing – it’s a critical asset that enables processing and decision making