Revolutionize Your Business Operations with B2b Sales Forecasting for Support

How to create outlook signature

[Music] the main point of this class is to understand the pros and cons of sales forecasting there is only one part in this class sales forecasting and before you like this video subscribe to my channel tell your friends about me make sure you check the assessment objective for this class foreign sales forecasting is all about predicting the future sales this is a set of techniques both quantitative and qualitative that are aimed at predicting the future sales of a product good or service there are a lot of sales forecasting techniques but the ones that will cover in IB business management syllabus are the following six techniques moving averages variations time series analysis simple linear regression from toolkit descriptive statistics from toolkit and market research from 4.4 in this class I will only talk about the first three because the remaining three sales forecasting techniques can be found in other classes in toolkit and in 4.4 before we continue one very important disclaimer calculations of moving averages and variations are not included in exams but you are expected to be able to interpret sales forecasting data however ever it is expected of you to perform sales forecasting techniques from the toolkit see simple linear regression and descriptive statistics so these three first sales forecasting techniques move in averages variations and time series analysis I will tell you how to do them how to perform them how to calculate them but you will not be asked to do that in the exam you might ask so why are we learning it then because if we don't learn it you won't be able to understand how it works and you won't be able to interpret this data so be patient and learn some new stuff about sales forecast 10. let's go so moving averages one thing that you can do is just record past data per year or per month or per week or per whatever time period and build a chart bundled a line build and Trend but this trend will look really jumpy it'll be like this so in order to smooth in the trend whoever is in charge of sales forecasting is usually calculating three part moving averages or four part moving averages part can refer to either year or month or week or two whatever time period you can say three year moving average which means that that would be average of three years or you can say three part moving average that would mean the same thing but what's important here is that the part does not have to be year it can be three year moving average three months moving average three moving average three day moving average or whatever so the overall name is three part moving average what part is is completely up to you so once again why we calculate three part or four part moving averages to make sure that the trend doesn't look like this doesn't look jumpy that it's more smoother this way it'll be easier to extrapolate the trend extrapolation is something that we learn in the toolkit and I will get back to you later but basically it means the trend for the future based on past data so the smoother the trend the easier it would be to prolong it if it looks like this then it's unclear where it's going that's it now let's see an example here you can see sales data in millions of rubles for 10 years if we just passed data for sales then the chart is going to look like this look at the Gray Line see it looks pretty jumpy going up and down up and down but you calculate three year moving average then the trend would look much smoother how to calculate three-year moving average we calculate averages of three years First Years one two three second years two three four third years three four five and etc etc so here you can see all the moving averages in the third column if we put these numbers on a chart then we'll see this blue line here that looks much smoother than the gray line which makes it easier to extrapolate the trend you can see this dotted line here this is extrapolation we just continue the trend for the future thus predicting the sales that's it this is how three part moving average works there's also four part moving average four four part moving average it's pretty much the same thing but instead of three parts Years days months whatever you use four in addition there's one more step you have to Center the average you also need to calculate the average of the moving average but that's Way Beyond IB business management syllabus if you are interested in moving the averages just look up four-part moving average if you want me to explain that leave a comment below I'd be happy to record another video but now I want to move on because three-part moving average is enough for understanding these sales forecasting technique the second sales forecasting technique is called variation variation is related to moving averages it refers to the difference between actual past data and the trend or moving average the blue line from the picture that I showed you before why do we calculate variations because if you know variations at different time periods you will know when sales fluctuate mostly when they differ mostly from the trend it can help you to predict future sales more accurately you will know when demand is higher or lower you will adjust your cash flow management or stock control importantly we will talk about this in more detail later at the end of this class but overall we use a variation because it basically helps with sales forecasting and marketing planning because it's good to know how different the actual sales are from the trend let's look at this picture we are continuing the previous example so we have 10 years sales three-year moving averages and variation which is the difference between sales and the trend or three-year average as we can see the highest variations are in years six and seven so one thing that the managers might want to do is to dig deeper and find the reasons why years 6 and 7 are so different from the trend so that they can predict future sales more accurately which brings us to the third sales forecasting technique that is related to analyzing all the reasons for variations and fluctuations it's called time series analysis Time series is basically a set of bust data recorded at regular intervals past data for our purposes is of course sales data and time series analysis is identifying the patterns in the fluctuations in the past data in order to have more accurate sales forecasting there are three main kinds of fluctuations seasonal cyclical and random seasonal fluctuations are caused by surprise surprise Seasons winter spring summer autumn for example if we take ice cream then apparently the highest fluctuation from the trend will be in the summer when most people eat ice cream another example could be clothing we can certainly say that the sales of warm clothing are higher in Winter than in the summer so that would be examples of seasonal fluctuations cyclical fluctuations are based on the stages of the economic cycle or the business cycle or the cycle of economic activity or the cycle of economic growth there are plenty of names for it it looks like this I'm sure you heard about it before all economies go through the same stages recovery then it reaches the peak then recession then trough and then again recovery Peak recession trough recovery Etc overall I think it applies to pretty much all the products we might say that people spend more money during the growth during the recovery in people spend less during the recession when economy is heading towards the trough in the last example of fluctuations is random fluctuations these are basically unpredictable not based on anything not based on the cycle of economic activity not based on seasons for example if for some reason people start buying ice cream in Winter then that would be a random fluctuation based on God Knows Why what reason in this picture you can see fluctuations for ice cream sales seasonal fluctuations where in the summer ice cream sales go up cyclical fluctuations where ice cream sales pretty much overlap with the business cycle and random fluctuations when for some reason ice cream sales increase in winter and spring once again you are not expected to calculate moving averages and variations but if you are provided with this data in the case study then you are expected to be able to interpret it and use it to analyze the trends and patterns and make some conclusions and judgments based on this data however this does not apply to whatever is in business toolkit this you are expected not only to understand and interpret but also to calculate perform outline Etc the two business tools from IB business management toolkit that refer to sales forecasting are simple linear regression and descriptive statistics within each tool there is a set of other tools so those tools within simple linear regression and descriptive statistics that you should pay particular attention to are extrapolation line of best fit correlation and averages mean mode and median please find the corresponding class in the business management toolkit in addition to that market research data is also used for sales forecasting what is market research and how it works we will learn later in unit 4 in class 4.4 market research it's entirely about market research so watch 4.4 whenever you're ready to now once we understand all the sales forecasting techniques and how they work we are ready to finally talk about advantages and disadvantages of sale is forecasting on the one hand sales forecasting assist marketing planning that we learned in 4.2 if you can predict some future sales you can adjust your markets and mix ingly marketing mix is something that we'll learn in 4.5 but for now it's just a set of decisions that a business has to make when selling a product decisions about product price promotion place and also for services physical evidence people and processes so how to make these decisions how to make the right decisions this is something that sales forecasting can help with in addition it helps to maintain liquidity liquidity is something that we learned in 3.5 if you know when demand is high you will make sure as a manager that you have enough cash to purchase raw materials and components to produce a lot of products in order to sustain in order to meet the demand of your customers if the sales are predicted to be low then you don't need to hold that much cash because cash is a depreciates an asset once again what's liquidity learning 3.5 in addition to control of cash and liquidity it also helps with stock control stock refers to finished goods components raw materials that you keep in storage before you actually produce and sell your products again if you know when demand is high you will keep higher stocks to make sure you can easily meet the increase in demand when demand is predicted to be low you do not need to keep stocks High because keeping stocks high is actually expensive you need to pay the storage fees you need to insure the stocks etc etc so in order to make it really efficient sales forecasting really helps with stock management and lastly sales forecasting is in a way planning and as we learned many times in all units of IB business management any kind of planning reduces risk because you're more prepared for the future you have Plan B plan C and Etc so this applies to sales forecasting as well it reduces risk now the disadvantages of sales forecasting sales based on the assumption that future depends on the past because all sales forecasting techniques work on this principle you take past data and you extrapolate the trend well in many cases this might be true but however it doesn't have to be this way there are things that cannot be predicted in there are situations when past data doesn't matter at all so this is the major limitation of sales forecasting it's based on past data that is used for future prediction that might not always be accurate in addition to that sales forecasting is just a forecasting it's a prediction it's about the future so in a way it is a guessing game which of course cannot be 100 accurate never additionally sales forecasting is time consuming and costly it's quite easy to forecast sales for a small business but think about a multinational company with millions of products millions of customers thousands of employees all over the world different markets that are also hard to Define that would be a nightmare so is it really worth doing it or not well let me know what you think and in addition to that even though there's more and more technology and artificial intelligence in everything including sales forecasting it is still to a large extent done by human beings and human beings are subjects to human factor and human mistakes and most importantly to human bias all managers would of course want to predict sales that are lower than they really think they are because this will put these managers in a good light they will say oh it was predicted that I'll sell for ten thousand dollars but eventually it turned out to be 20. see I'm a good manager please give me a bonus so is subject to bias and something that can be manipulated by unethical managers that is the end of 4.3 I hope you enjoyed this class please like subscribe tell your friends about me and have a look at the assessment objective make sure now you can discuss the benefits and limitations of sales forecasting that's it bye [Music] foreign