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34% of the top 50 U.S. retailers have reported poor forecasting accuracy<\/a>. Considering a deviation of 1% in either over-forecasting or under-forecasting can cost a company thousands, or even millions of dollars, you have to wonder why? Only about 60% of the top retailers rate their inventory forecasting software as \u201cgood\u201d or \u201cvery good\u201d. Demand forecasting is a business function that grows more complex as your supply chain grows in complexity and magnitude.<\/p>\n In this article, you will gain insights into the critical aspects of demand forecasting and planning, and how these strategies can significantly impact the profit margins of retail businesses. From the basics of demand forecasting to the latest tools and technologies, discover how accurate forecasting can positively influence your business decisions and overall success.<\/p>\n Key Takeaways:<\/strong><\/p>\n <\/p>\n Contents<\/p>\n \u201cDemand Forecasting refers to the process of predicting the future demand for the firm\u2019s product. In other words, demand forecasting is comprised of a series of steps that involves the anticipation of demand for a product in the future under both controllable and uncontrollable factors.\u201d – BusinessJargons.com<\/p><\/blockquote>\n True demand forecasting involves your entire supply chain. Everyone has to share information that increases demand visibility. It\u2019s a tough exercise, but when you can implement it, you have crystal clear numbers for your business in the near and mid-future.<\/p>\n You will likely have to develop trust spanning your entire supply chain, meaning with other organizations. Once you do, operations run smoother for everyone.<\/p>\n <\/p>\n BONUS:<\/strong> Before you read further, download our Warehouse Management Software Whitepaper to see how Logiwa uses real-time tracking to help customers get up to 100% inventory accuracy and increase shipments by 2.5x.<\/a><\/p>\n Effective demand forecasting and demand planning is actually a part of Integrated Business Planning or Sales, Inventory, Operations Planning. Your inventory accuracy<\/a> is one of three supply chain KPIs<\/a> that you\u2019ll use to measure your planning effectiveness.<\/p>\n Your business\u2019 bottom line depends on high forecasting accuracy. Unfortunately, customer demand is incredibly volatile, which can make forecasting difficult.<\/p>\n Besides historical sales data, you\u2019ll need to incorporate:<\/p>\n Many businesses struggle to keep accurate historical data, especially when they use an omnichannel sales strategy<\/a> .<\/p>\n A flexible inventory management system<\/a> would help you keep the numbers straight, in addition to facilitating daily operations.<\/p>\n We can tie a variety of problems to poor retail forecasting accuracy. By improving your forecasting accuracy, you\u2019ll be able to make informed retail business decisions. Basically, you\u2019ll run a better retail business because your data will give you a peek into the possible future. Demand forecasting for retail can help you with various areas of your business as they impact the customer experience<\/a>.<\/p>\n Demand management and forecasting helps you understand when your peak sales times are. When you anticipate product demand, you can bring in additional staff to handle the increased inventory.<\/p>\n Analysts suggested that the problem didn\u2019t stem from lack of inventory. They said that inventory sat on the warehouse shelves due to low-staffing issues. Walmart had apparently reduced the number of staff in some warehouses in an effort to control costs.<\/p>\n They failed to forecast how that staff reduction would impact their customers\u2019 in-store experience.<\/p>\n When you properly forecast your products\u2019 demand, you can use that information to make operational decisions.<\/p>\n When your customers look up at the shelves or on their screen and see you\u2019re out-of-stock, it creates a bad customer experience. It doesn\u2019t usually bother customers when you don\u2019t carry a product. However, seeing an empty shelf or out-of-stock alert causes friction in the customer experience.<\/p>\n Walmart customers complained of the same thing. So did Nike\u2019s customers in 2001 when they implemented demand planning software without enough testing. There was a glitch (or a few) with their new $400 million software that caused their supply chain to produce too few Air Jordans and too many Air Garnetts (we\u2019ve never even heard of those).<\/p>\n Nike recovered of course, but that\u2019s not the sort of hit most businesses can take. However, their stock took a hit, and their loyal customers weren\u2019t happy.<\/p>\n Sometimes, expedited deliveries are part of doing business. When they become a regular occurrence, you need to determine why. Some businesses are integrating expedited shipping as part of their business model<\/a>. However, if that\u2019s not your business model, then you aren\u2019t saving money.<\/p>\n Evaluate your supply chain to identify the failures in your process. If you can avoid the expediting costs, then you\u2019re spending money that can benefit another section of your business. These sorts of costs hurt your bottom line, making your business less profitable.<\/p>\n Besides strengthening your supply chain against weaknesses, you might also consider using a WMS that automatically reorders inventory based on inventory reorder points<\/a>.<\/p>\n When you accurately do forecast your retail inventory, you keep your inventory levels right where they need to be. You need enough inventory to satisfy the downstream demand, but overstocking leads to a variety of problems, such as higher carrying costs.<\/p>\n Excess inventory gathers dust and gets in the way of your warehouse employees, impacting their order picking productivity<\/a>. Your employees may need to clean off old inventory before it can be shipped. This can delay load times for the vehicles at your warehouse, leading to late deliveries and \u00a0unhappy customers.<\/p>\n In such a highly competitive market, can you afford to have unsatisfied customers?<\/p>\n The goal of\u00a0 demand forecasting and demand planning<\/a>\u00a0 is to predict customer demand as accurately as possible to avoid the issues we described above. Retail demand forecasting models are grouped into two categories: qualitative and quantitative. Quantitative methods rely on data, while qualitative methods rely on (usually expert) opinions.<\/p>\n Inventory demand forecasting methods are categorized as judgmental and experimental methods. They\u2019re usually used when historical data for your products aren\u2019t available. Like in the case of new products.<\/p>\n A judgmental method often used pulls on the opinions of available experts. You\u2019ll gather subjective assessments from suppliers, marketing, sales, and purchasing professionals. You may also try executive brainstorming, which has the goal of drawing on your executives\u2019 experience to create a collective perspective on future demand.<\/p>\n Delphi studies are an advanced method of quantitative demand forecasting<\/a>. Each participant will provide their opinion without collaborating with the others to avoid bias. Each person will then review the group opinions, altering their own demand projections until the group reaches a consensus. You\u2019ll have to do multiple rounds in order to reach that conclusion.<\/p>\n There are quite a few different qualitative methods, ranging from basic to complex. All of them can be very valuable in developing an accurate forecast.<\/p>\n Causal methods use a number of internal and external factors, such as price, legislation, and even the weather, along with another qualitative method to accurately paint a picture of future inventory requirements.<\/p>\n <\/p>\n Don’t Let Your Inventory Become a Liability:<\/strong> Poor inventory accuracy leads to a host of issues that cut into your margins. Learn how Logiwa integrates all your sales channels and provides real-time inventory tracking.<\/a><\/p>\n Projective forecasting methods are based on mathematical formulas, which can provide a more straightforward answer to your inventory forecasting needs. These methods use past data to estimate future demand. Demand forecasting software is often used, so we won\u2019t go into the precise formulas for each type. Moving average, exponential smoothing, and time series analysis are a few examples.<\/p>\n Life cycle forecasting can be useful for technology products or any inventory with a high chance of obsolescence. This type of demand forecasting tools accounts for the fact that demand changes throughout the life cycle of a product<\/a>. Accurately retail forecasting based on the life cycle of your products can help you keep even leaner inventory, and account for future releases of newer versions of your product.<\/p>\n Demand forecasting software usually has the ability to incorporate various forecasting methods to understand what your data is telling you. You need to know overall product trends, annual trends, and seasonal trends, which uses multiple forecasting methods.<\/p>\n When looking at your inventory trends, it\u2019s important to account for seasonality<\/a>. If you take the number of sales you\u2019ve had across the year and use the average as your inventory level, you\u2019re going to have too much stock some times, and too little stock at other times. Holiday decorations are a great example of this.<\/p>\n Brick-and-mortar and online stores sell a serious amount of Christmas decorations leading up to Christmas. They have sales on decorations at the end of the holiday season to clear all of that inventory out of their stores.<\/p>\n Have you ever seen Christmas decorations on retail shelves in May? The costs associated with carrying that item isn\u2019t worth the price.<\/p>\n Some products aren\u2019t as affected by seasonality, like diapers. Children wear diapers for the first 2-3 years of their lives, and people have babies year round. So demand is fairly steady.<\/p>\n Be sure to review your data to see which products are affected by seasonality and which are more steady. You shouldn\u2019t forecast for diapers and baby wipes the same way you would forecast for holiday decorations.<\/p>\n Seasonality is a change in demand on a periodic basis. Trends are a change in demand that occur for a variety of reasons, like a shift in consumer behavior. If a product has sold at a steady rate for years, and then demand increases, this is a trend. If you\u2019ve always sold a particular pillow, and then a celebrity posts about how wonderful it is on social media, you may experience a positive trend in sales.<\/p>\n Conversely, if a product gets negative press, like child labor being involved in the manufacturing, you may see a negative trend in sales for that product or even the whole brand.<\/p>\n Companies have always tried to get ahead of sales trends. The correlation between accurate forecasting and lower supply chain costs has long been understood. The advances in technology like artificial intelligence and data analytics have made it possible for companies to see accuracy rates like never before.<\/p>\n This doesn\u2019t discount the need for experienced personnel. It\u2019s not a man-versus-technology scenario. It\u2019s a humans-augmented-by-technology scenario.<\/p>\n In an interview for Demand-Planning.com, Dr. Chaman Jain, Editor of the Journal of Business Forecasting said \u201cI found an average company can save $3.52 mil. for every one-percent improvement in the under-forecasting error, and $1.43 mil. in improving the over-forecasting error.\u201d<\/p>\n The amount of savings that he notes here is massive, especially when you consider that for every 1% for either type of error, you\u2019re likely losing much more than that. You have to consider lost sales and lowered credibility as the impacts ripple to your customers or your suppliers.<\/p>\n The potential for supply chain savings outweighs the cost for tools like demand forecasting software. Which means you can\u2019t afford to ignore this supply chain and warehouse tech development. Because ecommerce, wholesale and even 3PL businesses big and small struggle with forecasting accuracy, expect to see investments of all kinds in this tech in the coming months and years. Even 3PLS within their 3PL software<\/a> offer basic forecasting for their clients.<\/p>\n As you can see, there are a variety of methods that you can use to in retail forecasting and inventory planning. No matter which process you use, you should approach your retail forecasting in a methodical manner. Here\u2019s our recommendation:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.22.2″ _module_preset=”default” width=”auto” custom_margin=”15px|auto|15px|auto|false|false” custom_css_main_element=”.hbspt-form .legal-consent-container a {|| color: white !important;||}” locked=”off” global_colors_info=”{}” global_module=”26788″ theme_builder_area=”post_content”][et_pb_column type=”4_4″ _builder_version=”4.22.2″ _module_preset=”default” use_background_color_gradient=”on” background_color_gradient_stops=”#481a96 0%|#200741 100%” custom_padding=”15px|35px|15px|35px|true|true” border_radii=”on|10px|10px|10px|10px” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_text _builder_version=”4.22.2″ _module_preset=”default” header_3_text_color=”#ffffff” header_3_font_size=”30px” header_3_font_size_tablet=”30px” header_3_font_size_phone=”20px” header_3_font_size_last_edited=”on|phone” global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n [\/et_pb_text][et_pb_code _builder_version=”4.22.2″ _module_preset=”default” text_orientation=”center” global_colors_info=”{}” theme_builder_area=”post_content”]\n
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1) What is Demand Forecasting?<\/h2>\n
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2) How Does Retail Forecasting Help You Run a Better Business?<\/h2>\n
Demand Forecasting Can Help You Manage Your Warehouse Staff Numbers<\/h3>\n
Inventory Accuracy Impacts Your Customer\u2019s Confidence in Your Brand<\/h3>\n
You Can Avoid Situations Where You Must Expedite Inventory<\/h3>\n
Keep Warehousing Costs Optimal by Holding The Right Amount of Inventory<\/h3>\n
3) Demand Forecasting Models<\/h2>\n
Qualitative Demand Forecasting<\/h3>\n
Quantitative Demand Forecasting<\/h3>\n
Causal methods<\/h4>\n
Projective forecasting methods<\/h4>\n
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Life Cycle Forecasting<\/h4>\n
4) Forecast and Demand Planning for Trends and Seasonality<\/h2>\n
Isn\u2019t Seasonality a Trend?<\/h3>\n
5) Demand Forecasting Tools<\/h2>\n
6) How To Approach Your Retail Forecast and Demand Planning<\/h2>\n
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Request a free demo to learn more about Logiwa WMS.<\/h3>\n