inlumi blog

A quick search on Google and you are overwhelmed with the number of articles written about how to motivate and engage your employees. These strategies can form the backbone of company culture – trusting, transparent, people-focused – but can also refer to various perks like private healthcare, team-building, and even breakfast every Friday morning. But one thing is for sure: in today’s digital work environment in which candidates drive the recruitment process, the cost of replacing a top performer who is unhappy is significantly higher than listening to their needs.

As consultants who drive optimisation and digitalisation, our solutions always look different since they are customised for a particular client. Nevertheless, applying a specific methodology will allow you to steer the project as smoothly as possible to ensure you meet the project goals within a specific timeline and budget. Agile and Waterfall are two very distinct —but valuable — methodologies that should be chosen depending on different priorities, teams, resources, and customer needs.

Nowadays we hear more and more about cross-functional partners or cross-functional teams in our business environment. While cross-functional teams have always existed in all industries, where people with different skills and knowledge have contributed to the success of a project, there is now a real increase in the cross-functional partners. This cross-functional partner is taking over the role of a cross-functional team, and in some cases leading these teams to success.

During the Climate Conference (COP26) in Glasgow, 120 world leaders gathered to discuss the urgency of acting on climate change. It became clear that we have a joint responsibility to address climate change to preserve the planet for future generations, with many countries aiming to reduce their carbon footprint significantly before 2030, and to have zero emissions by 2050. The key messages that came from the conference were clear: there is still a lot of work to do, and the time to act is now.

Artificial Intelligence (AI) is taking the world by storm. Enabling machines to simulate intelligent human behaviour, AI unleashes a world of possibilities for businesses to automate and optimise processes, as well as generating insights for better decision-making. Nevertheless, developing this cutting-edge technology relies on historical data generated by humans, and therefore risks reproducing discriminatory practices and harmful stereotypes created by those very humans. How can we ensure that we leverage AI in the right way?

With the advances in technology over the last two decades, Finance leaders can now benefit from a powerful set of tools to collect and analyse data, and to report and gain actionable insights about their businesses. That means both one-off and ongoing IT-run costs are increasing, and in its latest report, Gartner forecasts IT spend to grow a further 5% in 2022 alone.

The discipline of Planning, Budgeting and Forecasting has covered a lot of ground over the past 20+ years, sustaining a steady evolution and maturing into a fully-fledged, crucial element of Management Reporting and Enterprise Performance Management.

Let’s start with something we all know: people dislike change. While it’s easy enough to say ‘change is good’ from an outsider perspective, when it comes to actually implementing a change ourselves we suddenly feel differently. This is because change takes two things that are very difficult to part with: time and effort.

inlumi is proud to be sponsoring Mossy Earth’s Lesser Kestrel GPS tagging project. This project involves tracking the migration patterns of a unique species which has been facing a dramatic population decline. In July, the team has already tagged two juvenile birds, one of which is named Lumi, after inlumi.

In a world where imitation is increasingly achievable, the margins for an organisation to gain competitive advantage are decreasing. As such, organisations are using modern technologies and analytical tools to find opportunities for reducing costs and creating value. Some of the most popular methods to do so are data and process mining.