Data analytics applications focused on the needs of small & medium enterprises. How they can benefit from demand prediction, sales forecasting and data projections.
Way too many among the managers of small & medium enterprises feel they are too small or they are not yet prepared to benefit from applied data science. Sometimes they are right and sometimes wrong. This is rising the question, when actually a business is ready to generate more profits/savings out of their existing data? How big it should be before consideration of data crunching. If a manager doesn’t dig deep enough into capabilities of applied data science or doesn’t have data analytics expert or at least consultant by their side, it is quite easy to miss significant opportunities for positive change and growth. This blog post is focused on this specific perception.
Let’s focus on businesses taxonomy regarding of their data maturity. They are five (relatively broad) levels of business data utilization as you can see from the graphic bellow.
Q-Commerce is the natural evolvement of E-Commerce, especially in the grocery segment. The always-on culture of smartphones made us more immediate including our purchasing habits. The Q-Commerce segment grew rapidly during the COVID-19 pandemics due to its convenience and fast delivery, up to 30, or even 15 minutes in some instances. It is like the corner shop but at your front door. How nice, isn’t it?
How Q-Commerce is possible?
Unlike brick and mortar retailers, Q-Commerce vendors have a limited assortment and a bit higher but still affordable pricing. They rely on so-called Dark Stores, a small warehouse full of groceries located throughout the city. As bikes, scooters, and bicycles are faster in congested urban traffic, customers can expect delivery within half an hour or less.
The COVID-19 pandemic is unprecedented in the recent days cataclysm. Countries from all over the world found themselves in a wholly new and, in most cases, unexpected situations. It applies to not just governments and businesses but also consumers.
The retail sector has been shaken by the dramatic change that forced some retailers to close their outlets, others to shift to e-commerce, while other businesses are facing drastic demand surge. When consumer behavior is rapidly changing, the right retailers’ response is essential, and their future might be at stake.
A DIY retailer, for instance, has the potential to increase its sales revenue by 1 – 2% annually with price elasticity of demand application.
Meeting customers’ needs is essential for a retailer wellbeing. A retail business failing to do so will be simply pushed out of the market, soon or later. Some retailers rely on their gut feeling but as data analytics experts, we are perfectly familiar with Arthur Conan Doyle who once said, “It is a capital mistake to theorize before one has data”.
Just think of it! Without credit and lending businesses, we would not be able to buy a house or appliances when we need them. Business would not be able to grow, expand and innovate at the desired pace. Credit is the fuel of any country` economy and this is not a secret. But what is fueling credit and lending businesses? How do they decide if you are eligible for a particular loan or not?
It started in the 70`s when Bruce D. Henderson created the growth-share matrix for the Boston Consulting Group. Its aim was to help businesses to analyze a particular product performance within the entire product line. It is simple yet effective approach if correctly applied.
Restaurant owners and managers can benefit too. The growth-share matrix, also known as the Boston Matrix has its restaurants’ custom-made version, called menu engineering. It is a data-driven approach to boosting a restaurant` profit. In this blog post, we are going to share with you how to do it easy and effective as possible.
Boston Matrix is a simple analytics diagram displaying business data in a convenient manner to deliver insights to managers on the performance of a product in terms of profitability and sales volumes. This data visualization approach, also known as growth-share matrix or portfolio diagram can be applied not just in terms of product performance but also in terms of ranking almost everything, including customers, revenue sources, marketing activities, etc. It is suitable even for NGOs willing to be more efficient in fundraising.
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.
