Here are some introductory articles on the methods, tools and benefits of predictive analytics and demand forecasting. They are aimed at those new to the sector or keen to learn more - no data science or technical background needed (if we've done our job correctly).
We will keep adding to this page, so do check back.
29 January, 2020
Forecasting the future is of interest to probably every business, organisation and public sector service in the world. But it's hard.
For many (most?) organisations, forecasting means asking their finance team to collate historical data in a spreadsheet and apply some sort of multiplier. This might then be refined using individuals' judgement and intuition, followed by a debate and/or argument with the finance team...
7 February, 2020
In this article we are going into another level of detail, to talk about how not all predictive algorithms are equal. What follows is a quick-fire introduction to a few concepts.
Continuous vs categorical forecasting: There are two main types of predictive analysis: continuous and categorical. Continuous models are concerned with...
7 July, 2020
This article was written in the week the UK emerged from its coronavirus lockdown, with restaurants, pubs, hotels (and, yes, hairdressers) all reopening to a new socially-distanced world.
With such a huge dislocation occuring in virtually every organisation, there is understandable scepticism in the accuracy of any demand forecast. In this article we explain why we still believe Skarp can siginificantly improve the accuracy of your forecasts.
17 April, 2020
A few thoughts on how data science can help any organisation (big and small) improve performance, regardless of their in-house capabilities.
"Data science", "machine learning" & "artificial intelligence" are terms bandied around somewhat indiscriminately - but for the vast majority of organisations they belong in the 'sounds exciting, no idea where to start' box...
22 April, 2020
We set ourselves the somewhat ambitious task of explaining feature engineering (also known as feature extraction) and its role in predictive analytics and demand forecasting. Which sounds really dull, so we're going to talk about the weather instead.
Let's imagine that you work for a restaurant with an outdoor dining area (even if, at the time of writing, restaurants across Europe are closed...
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29 April, 2020
Quantifying return-on-investment from marketing activity is always a challenge. The classic approach is to use a holdout / control group, but here we discuss an alternative: using accurate forecasts as baseline against which to measure performance uplift.
Probably the hardest conversation for any marketing director is the one with the CFO. It goes something like this...
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31 March, 2020
Written in the first few weeks of the coronavirus lockdown, this article has a few thoughts on how to regain some form of accuracy in your organisation's forecasts, even whilst we remain in coronavirus lockdown.
At the time of writing, the UK feels like it's in a surreal freefall: deserted streets; police drones following dog walkers; breweries making sanitiser instead of beer. Every day brings new restrictions, budgets or branding...
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Skarp uses machine learning-powered predictive analytics to generate accurate, automated demand forecasts - and an explanation of what is actually driving performance.
By removing uncertainty and quantifying the impact of factors affecting performance, Skarp can reduce costs and improve customer satisfaction.
We offer a fully-manage d service, designed for organisations with limited in-house data science resources.
IDENTIFY PERFORMANCE DRIVERS
OPTIMISE INVENTORY & STAFFING
MEASURE MARKETING ROI
There is no setup fee or minimum contract term with Skarp, and we offer all new clients a proof of concept free of charge. We believe the accuracy of our forecasts will speak for itself.
