Digitise and Digitalise Your Data for improved Decision-making

Modern organisations and businesses suffer from information overload, and the inability to turn the available information into understandable and accessible knowledge, is one of the primary reasons why decisions are often taken that are not sustainable in the long term.

The solution to this problem lies in the digitisation, digitalisation and visualisation of your data, which will enable managers to take improved decisions – both for their organisation, and for the management of impacts on the environment, especially on water resources.

One of the seven guiding principles for sustainable water resource management is “access to knowledge“.  Knowledge that is based on verifiable scientific information about hydrological and ecological processes, as well as about socio-economic conditions and considerations, which should be accessible, not only to specialists and scientists, but especially to decision-makers and to potentially affected communities.

To deal with the information-overload and lack of knowledge that we are currently suffering from, we need to embark on a process towards the digital transformation of especially our environmental information.

At the Board meeting of the World Economic Forum, held towards the end of 2018, an important report entitled “Our Shared Digital Future: Responsible Digital Transformation” was tabled.  The foreword of this report states that such transformation would bring “tremendous benefits … (which) include creating significant new economic value, meaningful and rewarding employment, and new products, services and markets that contribute towards sustainability and societal value”.  It furthermore states that “from a business perspective, the first challenge is immediate and existential”, primarily because “digitisation is rewriting the social contract – changing the relationship between individuals and the state and individuals and business”.

These findings are especially true for the collection of environmental data and information.  Regulatory specifications from government agencies necessitate the regular collection of large sets of data, for example on volumes of water abstracted, the water quality in nearby water bodies, or on weighbridge loads.  The costs associated with increased volumes of water consumed, or volumes of effluents discharged, or with the establishment of an effluent treatment plant, implies that it should be a business imperative to not only collect this type of data on a regular basis, but also to store it, securely, in a digitised format, that can be readily accessible in a format that could both provide confidence in its usefulness as information to be used as the basis for management decision-making, as well as meet the requirements of regulators with an oversight role, such as funders or government agencies.

Digitisation simply means the process of converting paper-based data to a digital form, and its many benefits include increased efficiency, reduced human error, safer data storage, reduced operational costs, and the availability of data to be analysed and visualised into management information.

However, simply digitising existing paper systems will not magically change it into management information.  The process of analysing your data, once it has been digitised, is known as digitalisation, and although digitalisation is often used interchangeably with the term digitisation, it is not the same.  Digitalisation refers to the use of digital technologies to turn digitised data into actionable and accesible knowledge, which is aimed at addressing specific management questions, and managing specific risks.  Real-time reports and graphical dashboards of your interpreted data on environmental performance, will allow managers to address problems before they become critical.

This implies that, once environmental data has been captured in a digitised format, it needs to be digitalised into management information.  Replacing paper and manual data collection processes with digitised forms allows businesses to collect data in a format that can be mined to better understand process performance, causes of risk, and cost drivers, which leads to earlier risk identification, and improved risk management decision-making.  This entails the transformation of words and numbers into graphs and reports that can be quickly prepared, and easily understood by both business executives, and community representatives, who are not necessarily environmental managers.

And this, digitalisation of data, presents the biggest hurdle for many an organisation to overcome:  Many organisations have digitised, and changed from paper-based forms to electronic forms and other types of electronic data collection and storage systems, but few have implemented digitalisation systems that can convert the collected data into visualised and accessible knowledge. Employees have to spend hours on a spreadsheet to create one time-series or bar-chart for a single set of data, and then have to replicate the exercise for twenty variables at just ten sampling points.

Because the mining of collected data, and the conversion thereof into visualised management knowledge, are tedious and time-consuming, the net result often entails that data is collected, simply for the purpose of collection, and never changed into a usable format, where it can actually add value to the business, and inform management decision-making.  Water quality laboratory reports are send to government agencies without any interpretation, or often compared against incorrect limit values as many laboratories compare water from environmental systems against standards for treated potable water (a scientifically flawed practice), which can lead to legal risks and liabilities for the mine.

This implies that the valuable information contained in the data is “lost”, because the digitised data has not been digitalised and visualised into management information.

The digitisation, digitalisation and visualisation of environmental data are therefore critical components of improving environmental performance, and preventing environmental liabilities.

Objectives of a data-transformation strategy

The objectives of a data-digitisation and digitalisation strategy should include the following:

  • Reducing the time and effort required to capture environmental data and documents, and ensuring that environmental data are captured as far as possible in a digital (and not paper-based) format, by making use of custom-made Apps (such as our WaterMonster App);
  • Providing a centralised repository for hard and soft data generated through the monitoring of various environmental aspects, including, but not limited to, water quantity and quality, waste transport and disposal, air quality (including meteorology), and other environmental aspects such as biomonitoring;
  • Ensuring control over the quality of the data in the repository, with the ability to prevent statistical outliers from influencing overall datasets, while keeping outlier datasets within the repository, unless it is deleted permanently for good reason, which is recorded on the system;
  • Facilitating control over disparate compliance specifications and reporting requirements;
  • Facilitating control over environmental reporting deadlines and/or monitoring schedules as required under contractual obligations and/or legal compliance specifications; and
  • Generating different types of outputs on different sets of environmental data, including reports and graphs in different tabular or graphical formats (such as our Leguaan Service), as well as standardised letters, emails, alerts, etc., in order to fulfill contractual obligations and/or legal compliance specifications.

Such a environmental data repository should typically facilitate the digitisation and digitalisation of, quality control over, and the generation of reports and graphs on, the following groups of environmental data:

Digitalise your environmental data

Digitisate and digitalise for improved environmental decision-making – start today!

Get in touch for a quote to help you digitise and digitalise your environmental data and information into visualised management knowledge, that can help you make decisions towards a sustainable future, and reduce your environmental risks and liabilities.

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