Why Organisations Need an Outcome-based, Data-First Approach
An underground piping systems suddenly burst into flames in the still of the night, plunging the surrounding areas into complete darkness.
Meanwhile, a consulting firm got alerted that their network are compromised and their clients data may be leaked.
Today, such incidents are increasingly happening, and when occur, will cause disruptions to business operations and worse, damage to customer trust and business continuity.
Could such worst-case scenarios be mapped out earlier by detecting and responding in advance, and are there ways to prevent the incidents?
The simple answer is yes. Organisations that adopt an outcome-based data-first approach in solutioning could avert such mishaps or realise new levels of operational efficiencies. But there is a caveat: they need to have clarity on what are the scenarios to prevent, what positive outcomes or even, growth opportunities to attain, and what are the relevant and usable data to collect.
Many business leaders recognise the value of data and prioritise digital transformation. But too often, data is collected for data’s sake. This leads to data wastage and worse, less-than-ideal solutions due to irrelevant or insufficient data.
Rather than fixate on collecting as much data as possible, businesses should ask themselves what they hope to achieve with the data. Such clarity of intent is critical to developing solutions – from engineering ways to preventing incidents to enhancing business performance.
Businesses ought to be laser sharp in defining intended outcomes and the type of data required to achieve these outcomes, before adopting a data-first approach.
What is a data-first approach?
Today, as more organisations recognise the true value of data, adopting a data-first approach could be the best way to solve many challenges.
For instance, the piping systems failure incident could be averted by monitoring data from sensors placed within critical installations. This could include scrutinising temperature or pressure level data – a higher-than-normal temperature or pressure level could indicate a potential problem that needs fixing now.
Likewise, with the increased in remote working and digitalisation, the cybersecurity team should have reassessed the new risks, and identify the new data points and weave into their cybersecurity risk patching and management workflow.
With the right data crunching in placed, predictive maintenance and responsive cybersecurity could be taken to prevent a catastrophic failure.
Unleashing the hidden potential of data
The highly interconnected world of today has sent defence, public safety and security and businesses on a quest to transform so they can better predict the unknown, prevent and recover from incidents expeditiously.
But beyond collecting the right data, it is more important to know how to interpret it and deliver actionable insights that could improve the performance of systems, reduce operational costs and enhance collaborations.
By gaining a mastery of our data, we need to think about what, when and why we need the data, and deploy the right solutions by looking at the right data points and managing the data efficiently. This way, we can bring about a real impact to the world.
Take pre-hospital emergency care for instance. When we recently co-developed the Operational Medical Networks Informatics Integrator (OMNII) platform that links pre-hospital emergency care providers with hospitals, we took a data-first approach with the aim to deliver faster and more seamless patient care by providing the right data to hospitals before patients are admitted.
Making data work for you
Data is voluminous. If it is not sourced and used in its rightful place, it will be wasting much resources and time. Here is a look at what we have seen as best use of data in the right context and usability for impact.
Data and Video Analytics
By detecting and analysing abnormal patterns in data – video, imagery, sound and social media sentiments, AI-driven surveillance powered by deep learning and machine learning automatically forms linkages and detects anomalies across public safety and security, healthcare, and operational applications. This could be detecting unknown suspects or finding people and vehicle of interests, identifying potential fraud, and providing better resources allocation and pre-emptive maintenance.
To spotlight, we have seen how Tan Tock Seng Hospital has successfully optimised their bed and resources allocation through the good use of data.
Satellite Imagery Data
Imagery data captured from satellite helps fight climate change by predicting forest fires, tackling maritime challenges such as illegal fishing activities through geospatial monitoring, and promoting sustainable development through better urban planning.
At our ST Engineering Geo-Insights, Electro-Optics and Synthetic Aperture Radar (SAR) satellite data are used to detect fire and burned area, providing real-time user notification and allowing persistent monitoring of clouds, haze and smoke plumes.
Through analytic algorithms in the cloud data in both private and public cloud can provide new insights. Improvements can be made to the application performance and optimise IT costs. Cloud capacity analytics allows users to scale and have dynamic resizing of resources.
This helps to fully optimise and leverage the agility, flexibility and scalability of cloud hosting platforms for better governance and accessibility, and to accelerate innovation.
As companies begin to harness the power of cloud technology to digitise and transform their operations, they now need to think about the next step: how to protect their data and scale up operations. To do that, having a hybrid multi-cloud strategy – using multiple public and private cloud services that are optimised, secured and well governed is key. At ST Engineering Digital Systems, we have developed the AGIL™ Cloud Management Platform Suite – a platform that designs, builds and manages secured multi-cloud services.
The close study of threat data can help build up resilience and pre-emptive capabilities against cyber-attacks from organised and lone wolf attackers. Proactive detection and prevention of attacks ensures a safer work IT and ops tech environment.
In the area of Cyber Forensics, we emphasise the need of having a well-established sound methodology to acquire, analyse, document, and present evidence. However, cyber adversaries are merciless and do not follow any rules when they carry out cyber-attacks and commit cybercrimes. That is where we combine findings with strong reasoning to focus on feasibility, probability, and correlation analysis is necessary to uncover the truth for a cyber-resilient operations and infrastructure.
Advancing new technologies
As we look towards a future where organisations adopt an outcome-based data-first approach, disruptive technologies like connected end-to-end supply chains can leverage data to improve processes and decision-making across the supply chain.
Likewise, as autonomous technology and robots play a bigger role in our daily lives, insights drawn from a data-first approach will help to perpetuate advancements of these technologies.
All these will be catalysed further by improvements in communication technologies such as 5G and satellite communications – with faster bandwidths, lower latencies and better interoperability between systems.
In the e-commerce space, outcome-based data-first approach can be adopted to understand consumer behaviour and preferences better. Data collected are analysed using data analytics and artificial intelligence and with insights generated, organisations are able to develop and offer better and more attractive products to consumers.
Hence, for a data-first approach to be truly successful, companies need a cultural shift in their mindsets to find and adopt data-driven solutions. Only then will data mastery lead to an even faster, safer and a more efficient and sustainable future.
Digital Tech | Cybersecurity
February 2021 • 8 mins read