Engineering and Infrastructure
North Africa | Remote Survey
A combination of Covid-19 and an uncertain security situation left our customer unable to send its engineers to a large power station in North Africa.
The customer needed a way of collecting information relevant to the status and progress of the development of the power station. Conventional methods - of sending a locally engaged contractor to inspect the site - had failed and had not delivered accurate, timely or accountable information.
ExInsight's powerful software has been designed to provide geo-referenced and timestamped information. Equipping a locally engaged contractor with our phone-based app, the engineering company was able to ask questions and get answers remotely, with accountability and assurance built into the process.
The engineers, based in a European country, were able to send a mix of subjective and quantitative questions to the field, and receive responses back in near real-time. Each response was tagged with a location and timestamp to provide certainty that the surveyors were where they were supposed to be at the specified time. The surveyors were also able to attach imagery as supporting evidence to help the engineers better understand the situation remotely.
The engineering firm was able to monitor the progress of the development and operation of the power station remotely at a time where they couldn't easily send engineers internationally. ExInsight's cutting edge software provided them with assurance and advantage and allowed business continuity in an otherwise difficult time.
Oil and Gas
East Africa | Situation Awareness
An oil and gas company, operating in a challenging part of Africa needed to understand disparate data on impediments to its operation including the weather, the terrain and the security situation. Data was previously held by separate departments and wasn't easily interfaced or networked. Data visualizations were presented in PDF form and could not be interrogated for more detail.
Our software is used by the company to collect, collate, analyse and present information to stakeholders to help them better understand their situation.
The team is able to quickly and easily upload open source data sets relevant to their operation alongside proprietary data sets to provide a unique understanding of their environment. They can do so with very little training and do not need to recruit additional human resource to do so.
The team is able to work collaboratively across three continents and has achieved a common operating picture. They use the software throughout their working day to better understand a dynamic situation and gather weekly to review the situation where they are able to drill down and filter data in real-time, letting them ask ever more granular questions and get informative answers.
Global | Supply Chain Preparedness
A consulting company was tasked with cataloguing suppliers to the United States military as part of a global search for vendor support. Previously, information was catalogued in spreadsheets and then incorporated into PDF documents. By the time the information was reviewed by the end-users, it was out-of-date, and could not be filtered by place or by attribute.
Our solution lets our customer collect and collate information easily. The team sourcing the data can enter the information via easy-to-use forms to ensure data validation, or can link to spreadsheets or third-party directories to incorporate data in bulk.
Suppliers can be given attributes such as the type of product they offer, their readiness, their capacity and location which forms the foundation of analysis thereafter.
Our customer has information available on demand instead of information locked away in PDF. They can easily drill down to a specific geography, filtering the suppliers in that area in response the end-users needs, affording them with a better-than-ever understanding of their supply chain preparedness.
Somaliland | Remote Surveys
A leading provider of research and development services was tasked with an academic survey of communities in rural Somaliland as part of a project to assess the impact of climate change on farmers in East Africa.
In addition to the existing complexities of conducting surveys, this particular survey would occur in a challenging rural environment. The questions would not be asked in English. There was also a short lead time to setting up the survey and gathering data.
Previous efforts to complement the survey with technology and tools had been manual and repetitive. Other attempted solutions were clunky, difficult to use, and not designed for low-bandwidth or difficult environments. Existing processes were time-intensive, with manual note-taking, the transfer of data to an electronic format, and the manual creation of charts.
The team needed a system that was easy-to-deploy, intuitive, automated, visual, and designed to work in low bandwidth environments.
Our solution is designed to be easy-to-deploy. That means that the team did not have to wait weeks or months to set the system up and prove the concept. They could instead do so within minutes, ensuring buy-in. The collaborative nature of the tool meant that team members could work together to review the survey from both the United Kingdom and Somaliland.
The intuitive nature of the system also meant little training was needed. The team was up-and-running and created their first survey within minutes of the training starting. Online videos via our online help and training portal.
The phone application was able to cope with the remote aspect of the survey. Multiple surveys could be conducted and saved offline before later synching upon reaching connectivity again.
As the project developed, our team worked with the customer to enhance the structuring of the data. This led to an increase in the number of quantitative outcomes of the system and an improved ability to slice and dice the data.
The visual aspect of the system led to the results of the survey being presented in a mix of tables, maps and charts. These views of the data were generated by the system automatically, further reducing the time it takes to interpret and analyse data by removing the data wrangling part.