At A4E we are strong believers that data analytics is capable of bringing improved business efficiency in any industry or sector including the smallest one. That is why we created a webinar dedicated to pastries and bakeries in order to help them limit waste and boost sales at the same time. This way we shared useful insights on how to achieve meticulous planning balancing perfectly between supply, demand, production time and shelf life.
Like it or not, we all are living in a world where many people are starving while in the same time a tremendous amount of food is wasted by consumers, retailers, manufacturers, etc. Food wastage is a problem not just because is a missed opportunity for people in need. It is an issue because wasted food is incinerated in combustion facilities or is stored in landfills. Once in landfills, the food breaks down to methane, which is a strong contributor to the greenhouse effect boosting hazardous climate change. Speaking of food waste we should know that throwing an apple means we are spilling about 100 liters of water, needed for its growth. The water footprint of a beef is more than 7 tons of water.
On May 18th, 2017 we are going to make quite useful webinar targeted to bakery, pastry & cake shop business owners. Its focus is on different factors affecting sales, profitability and the tiny balance between demand and supply. We all know this is crucial if you want to provide your customers with fresh production.
Elon Musk and his Tesla Model S started it all. The premium electric sedan was equipped with advanced and self-learning Autopilot system, which can take the chauffeuring work out of the driver. It was a complete breakthrough because if it works as good as it should; it is going to change driving forever. It is all because of Artificial Intellect (AI) and the way it works fueled by data sensors and powered by video analytics. And since we have, to be honest, it wasn’t started by Elon Musk but the automotive industry itself. It doesn’t matter if we talk about rain sensing wipers (Cadillac) or adaptive cruise control (Mitsubishi) or lane departure systems (Mercedes-Benz). Such systems work with predefined events with some variables in the input data and one particular, predefined outcome.
Data is all around nowadays so it will be wise to explore how beneficial it might be. Unfortunately, tourism is among the sectors where big data analytics exploitation is not at its best. That’s why we would like to share some insights coming right out of our data analytics startup enthusiasm.
Big data and predictive analytics have a lot of applications, including sales forecasting, marketing and strategy optimization, machine maintenance, even sports and design. Police and security experts already know that big data and predictive analytics might be extremely helpful in fighting and preventing crimes. We are going to explain how they do it.
We don’t know if you know but a few years ago, the major music labels had pretty sweet business. They profited from any single or album, not matter it was vinyl, CD or even cassette. It is not like this anymore. MP3, torrents, piracy, streaming, and video sharing networks killed this particular business model. What music labels did to stay afloat? They asked data analytics for some help. And they were not alone – a lot of businesses emerged and shaped their models by applying data analytics to music services. We are going to explain this.
The sinking of the RMS Titanic is probably the most tragic event in the modern maritime history. It was not the deadliest though but it became the symbol of the human bigotry in terms of technical advancement. Back in 1912, Titanic was the largest, and most luxurious ocean liner ever made. She was claimed to be unsinkable. And she sank on her maiden voyage to New York.
Nowadays, mankind possesses a tremendous number of data, regarding many real-life phenomena. The availability of such a source of information is the main premise for the wide spread usage of the data-driven modelling. When account for more factors in the model development, this usually leads to a better ability of the model to represent the specifics of investigated system. Naturally, in fields like economics, society, medicine, etc. the models are with many inputs and many outputs (MIMO).
It is a common conception that data analytics is the next big thing for many of industries. Restaurants are no exception and this is visible. This blogpost is not aimed at pointing the benefits of restaurants sales forecasting, a tedious task we`ve already created a solution for. Nor to highlight what is restaurant data analytics all about. Our goal today is to share with you real-life use cases for data analytics. Restaurant owners & management teams – just take a look and pick some really nice restaurants data analytics ideas!