Data analytics for good – the next frontier
In 2018, data visualisation company DOMO predicted that by 2020, 1.7MB of data will be created every second for every person on earth. The New Year is now only one month away and this explosion of data is showing no sign of slowing down. As digitalisation becomes the norm across more industries and IoT adoption continues, even more data will be generated. Industries like healthcare and manufacturing have been turning data into insights that drive improvements to customer service, processes and products. Outside of these use cases, could this data driven approach also be applied to tackle social challenges?
Moving beyond the enterprise
It would be short-sighted to assume that data analytics can only be relevant within the enterprise. Improved connectivity and advances in IoT is creating vast volumes of data. As more people interact with these connected devices, the data generated will increase exponentially to represent every aspect of society. This will enable us to gain a better understanding of how processes work across myriad areas of modern life, granting us the ability to then use those insights to address existing and future problems. Aggregated and anonymised large-scale data has the potential to generate immense positive social impact.
For example, managing the aftermath of natural disasters can consume resources when time is precious. Planning aid in advance is key, and data analytics can be used to inform a plan to assist those in need. Governments and NGOs need to know where the impacted people are, in which direction they are moving and how the environment is changing. Only then can they respond effectively and efficiently to the effects of the disaster.
In a similar way, data analytics can be applied to protect public health by predicting the spread of a pandemic. Accurate predictions allow authorities to put measures in place which mitigate the effects and control the incidence of new cases.
Closer to home
Data can make a difference on a global scale, but what about in urban centres? Today, 55% of the world’s population lives in urban areas. This proportion is expected to increase to 68% by 2050. That’s another 2.5bn people dwelling in urban areas. This increase will place significant demands on infrastructure, retailers, banks, healthcare systems and educational institutions. In addition, preventing crime will also be a top priority. There is the potential for huge social impact, improving the management of cities and the quality of life of their citizens. For example, data collected by law enforcement can improve safety by better predicting crime spots and implementing measures such as improved lighting or CCTV.
Preparing for this scenario begins now, and it starts with understanding the movement of people. Governments and businesses alike can use this information to make significant decisions. In transport, for example, it can inform where to build bridges and footpaths or place electric car charging points.
The success of these initiatives relies on accurate insight into the needs and habits of urban populations. This must start with democratising access to population data intelligence, in a secure and anonymised way that protects the privacy of future citizens.
Keeping data private
The main concern about widespread data collection is data privacy; many high-profile companies have come under scrutiny for their use of customer data. However, it becomes more concerning when it is related to sensitive information, such as individual location or health status. Where will this data be stored and how will it be collected? Who will ultimately be responsible for keeping it safe from malicious actors? How can citizens be assured that their data will be anonymised and only be used for the stated purpose? The answers to these questions will affect the extent of the public’s support. Transparency in communicating with the public will be critical to the success of any data analytics initiatives, even if the purpose is for good.
Working together to keep data safe
Unlocking the full potential of data will require a concerted effort between different organisations. Those who collect the data must work together to ensure the insights are used by the most appropriate organisations who are able to effect change.
Vodafone is part of a wider alliance – the GSMA’s Big Data for Social Good initiative – where mobile operators share insights with NGOs to build an ecosystem that supports timely planning and response. Location intelligence – where location-based insights are used to solve problems and identify new opportunities – plays a role here, in building a safer, more sustainable world.
The increasing digitisation of industries provides the best opportunity for data to be mined for social good, as a positive ‘side effect’ of collection. In addition to making services more efficient, streamlined and personalised, the same data can be used to predict how populations move and react. As urban areas grow, these insights will be critical to informing how the safety and health of citizens will be managed. It is important that the right decisions are made now, regarding data collection and analytics. Only then will we be prepared to tackle the social challenges of the future.
Intelliwave SiteSense boosts APTIM material tracking
“We’ve been engaged with the APTIM team since early 2019 providing SiteSense, our mobile construction SaaS solution, for their maintenance and construction projects, allowing them to track materials and equipment, and manage inventory.
We have been working with the APTIM team to standardize material tracking processes and procedures, ultimately with the goal of reducing the amount of time spent looking for materials. Industry studies show that better management of materials can lead to a 16% increase in craft labour productivity.
Everyone knows construction is one of the oldest industries but it’s one of the least tech driven comparatively. About 95% of Engineering and Construction data captured goes unused, 13% of working hours are spent looking for data and around 30% of companies have applications that don’t integrate.
With APTIM, we’re looking at early risk detection, through predictive analysis and forecasting of material constraints, integrating with the ecosystem of software platforms and reporting on real-time data with a ‘field-first’ focus – through initiatives like the Digital Foreman. The APTIM team has seen great wins in the field, utilising bar-code technology, to check in thousands of material items quickly compared to manual methods.
There are three key areas when it comes to successful Materials Management in the software sector – culture, technology, and vendor engagement.
Given the state of world affairs, access to data needs to be off site via the cloud to support remote working conditions, providing a ‘single source of truth’ accessed by many parties; the tech sector is always growing, so companies need faster and more reliable access to this cloud data; digital supply chain initiatives engage vendors a lot earlier in the process to drive collaboration and to engage with their clients, which gives more assurance as there is more emphasis on automating data capture.
It’s been a challenging period with the pandemic, particularly for the supply chain. Look what happened in the Suez Canal – things can suddenly impact material costs and availability, and you really have to be more efficient to survive and succeed. Virtual system access can solve some issues and you need to look at data access in a wider net.
Solving problems comes down to better visibility, and proactively solving issues with vendors and enabling construction teams to execute their work. The biggest cause of delays is not being able to provide teams with what they need.
On average 2% of materials are lost or re-ordered, which only factors in the material cost, what is not captured is the duplicated effort of procurement, vendor and shipping costs, all of which have an environmental impact.
As things start to stabilise, APTIM continues to utilize SiteSense to boost efficiencies and solve productivity issues proactively. Integrating with 3D/4D modelling is just the precipice of what we can do. Access to data can help you firm up bids to win work, to make better cost estimates, and AI and ML are the next phase, providing an eco-system of tools.
A key focus for Intelliwave and APTIM is to increase the availability of data, whether it’s creating a data warehouse for visualisations or increasing integrations to provide additional value. We want to move to a more of an enterprise usage phase – up to now it’s been project based – so more people can access data in real time.