Getting demand right – or getting it wrong – can have a significant impact on customer perceptions of your brand, particularly in this age of instant gratification. The need for agile, accurate demand planning has never been greater. Predicting forward-looking demand signals and shifting consumer demand patterns to recommend balanced, profitable commercial
Search Results: demand planning (318)
The past 20 months of disruptions caused by COVID-19 have been a wake-up call for retailers and consumer goods companies. Unpredictable market trends have caused havoc with categories, brands and products making it harder to predict supply requirements. All of these changes have given rise to the need for consumption
The social and economic impact of COVID-19 has dramatically affected supply chains and demand planning across all industries. Then there’s the Amazon effect, which has led to sky-high consumer expectations of the ordering and delivery process. Demand planners for retailers and consumer goods companies have quickly realized they have no
The need for agile, accurate demand planning has never been greater. When considering migrating your demand management application to a cloud-native solution, you might experience platform management challenges ranging from lacking the resources needed to oversee application operations, to manipulating maintenance tasks that may distract from growing the business. Why
On September 2 (3pm UTC / 11am EDT), I'll be joining Jonathon Karelse, CEO of NorthFind Management, for an interactive "fireside chat" on the application of Behavioral Economics in demand planning. This is part of the Foresight Webinar Series, and registration is free. Since we first met at an Institute
The COVID-19 pandemic has revealed the vulnerability of pharmaceutical supply chains. Pharma companies are focusing on risk management to improve the resilience of their networks. Most of the measures they will take, including on-shoring, over capacities and redundancies, will lead to higher costs. To decrease inventory levels across these new
Applying machine learning approaches to forecasting is an area of great research interest. Progress is being made on multiple fronts, for example: In the M4 Forecasting Competition, completed earlier this year, the top two performers utilized machine learning with traditional time series forecasting methods. At the link you'll find full
If you think machine learning will replace demand planners, then don’t read this post. If you think machine learning will automate and unleash the power of insights allowing demand planners to drive more value and growth, then this article is a must read.
Omnichannel Analytics are helping companies uncover patterns in big data to improve the customer experience. Using those insights, companies can anticipate what consumers are planning to purchase and influence that purchase in real time. Companies are experiencing unprecedented complexity as they look for growth and market opportunities. Their product portfolios are
Using the past to predict the future is a time-honoured practice. Of course it can backfire — which is why financial services firms are required to inform us that ‘past performance is not a guide to future performance’ — but customer behavior is often remarkably consistent. Which is why the
Citing online job postings reviewed by talent data firm Wanted Analytics, and a Software Advice blog by Michael Koploy, APICS e-News reports that "Demand planning analysts" are hot -- one of the five hottest careers in logistics. (Free subscription to APICS e-News) Clearly, APICS means there are a lot of good jobs
I was recently told that an organization had tried to implement AI for forecasting in supply chain but had failed due to poor data. This got me thinking about exactly what the impacts of poor data would be. And whether the approaches I had applied elsewhere could help. It's probably
Before the outbreak of COVID-19, demand planning hardly ever matched actual sales. But since the virus reached Europe, the level of sales in different product categories became even more difficult to predict. How could the garden centers have imagined that consumers would invest their money in a roof, pavement or
I've never been much of a fan of forecasting approaches to intermittent demand. In situations like intermittent demand (or other areas where we have little hope of reasonably accurate forecasts), my thinking is "why bother?" If we can't expect to solve the problem with forecasting, we need a different approach.
Fueled by a number of factors, including a global pandemic, data analytics skills are in high-demand. Organizations like the Youth Employment Services (YES) are well aware of the abundance of data and its growing complexity. That's why they partnered with SAS last year to provide free learning pathways to help
Demand management concepts are now over 30 years old. The first use of the term "demand management" surfaced in the commercial sector in the late 1980s and early 1990s. Before that, the focus was on a more siloed approach to demand forecasting and planning that was manual and used simple
Thanks to COVID-19, companies have experienced how challenging it can be to plan and maneuver their supply chains around an unforeseen disruption. While the pandemic was a once-in-a-lifetime event (we hope), the unfortunate truth is that less severe events have overwhelmed or undermined demand and supply planning in the past
What if you had a technology solution that creates a real-time link between the customer demand signal and what's happening on the ground? What if plans that are being steered centrally could finally be connected to every shipping lane, while simultaneously, creating cost saving carrier adjustments? The first-of-its kind integration
Depending on who you talk to, you'll get varying definitions and opinions regarding demand sensing. Anything from sensing short-range replenishment based on sales orders, to the manual blending of point-of-sales (POS) data and shipments. But a key component for retailers and CPG companies is accurately forecasting short-term consumer demand to
Rapid demand response forecasting techniques are forecasting processes that can incorporate key information quickly enough to act upon in real time by agile supply chains. Retailers and consumer goods suppliers are urgently trying to determine how changes in consumer behavior will affect their regions, channels, categories, brands and products during
In many countries, retail has been right at the centre of the coronavirus storm. Some retailers – those selling essential goods – have been unable or barely able to keep up with demand. Other sectors, notably clothes and luxury goods, have seen a complete drop-off in demand. Some retailers have
Many of us are currently working from home and getting adjusted to this new way of working. If you’re an employee working on the shop floor of a manufacturing facility, however, working from home is not an option. Among the many hard decisions manufacturing leaders have had to make during
Our customers confirmed that it really does not matter to them whether the selection of goods, pricing or advertising are chosen by machine, or by a human buyer.
Is it getting harder and harder to find empty Excel spreadsheets cells, as you run out of columns and rows? Do your spreadsheet cell labels have more letters than the license plate on your car? Do you find yourself waking up in the middle of the night in cold
El 2020 inició con la realización del NRF 2020, para muchos el principal evento de innovación y tecnología aplicadas al sector retail o comercio minorista en el mundo. Más allá de visiones como las del Experience 2030, The Future of Customer Experience is now o de charlas y exposiciones inspiradoras
If you're looking for advice on developing an analytics strategy, there's no shortage of resources, including this from SAS: Building your data and analytics strategy. If, on the other hand, you're looking for advice on how to apply analytics to strategic planning, your search has likely to come up wanting.
Planeación y optimización, la fórmula para las empresas demand-driven Sus clientes tienen mucho qué decir; más de lo que usted cree. ¿Los está escuchando? No necesariamente tiene que charlar con ellos cuando realizan una compra –en la tienda o el portal de comercio electrónico. Lo que comunican va más allá
Just last week, Walmart announced that they'll be testing inventory management robots. These robots will cruise store aisles, scanning shelves to identify out-of-stock products and other issues. According Reuters, Walmart is testing these camera-equipped robots in a handful of stores, but plans to expand the test to 50 stores. We
Depending on who you speak with you will get varying definitions and opinions regarding demand sensing and shaping from sensing short-range replenishment based on sales orders to manual blending of point-of-sales (POS) data and shipments. Most companies think that they are sensing demand when in fact they are
Let me start by posing a question: "Are you forecasting at the edge to anticipate what consumers want or need before they know it?" Not just forecasting based on past demand behavior, but using real-time information as it is streaming in from connected devices on the Internet of Things (IoT).