ForecastingThis week, we learned about the importance of forecasting future sales and profit for companies. Of course, there are many factors which can affect the reliability of these forecasts, such as interest rate fluctuations, competitive innovations, new customers, etc. But still, finance leaders must make every attempt to build their business strategy on forecasts that are as accurate as possible.
NOTE: If you work in an organization where you have no access to sales and profitability data, you may focus your post on the predictability of other variables that impact things like staffing, product delivery or other operational functions.
Post your initial response by Wednesday, midnight of your time zone, and reply to at least 2 of your classmates’ initial posts by Sunday, midnight of your time zone
1st person to respond to Deborah
Hello JP and Classmates.
One of Walmart’s abilities to forecast future sales and profits, and the most significant variables that are difficult to predict. Walmart wants to tap into its greatest asset, like chasing new business opportunities from bulking up its ad sales to becoming a major health- care provider.
Last week the CEO talks about sustaining momentum as some coronavirus pandemic-related tailwinds fade and online sales as well.
This would discounter a weave together, and diverse services customers want, from credit or debit cards, buy groceries and also increase investments to cater to customers, changed shopping habits. Walmart talked about scaling new capabilities and businesses and designing them to work together, this would help them to build an ecosystem of products and services to deepen loyalty and win more customers.
The results and its forecast for moderating sales in the year ahead prompted a sell-off. Walmart shares closed Thursday down 6.48% to $137.66. Its market value is now $389.48 billion. In the fiscal year, Walmart grew its revenue by $35 billion, but higher sales alone won’t get it to higher profits.
Walmart relies on big data to get a real-time view of the workflow in the pharmacy, distribution centers, and throughout our stores and e-commerce. (https://corporate.walmart.com/newsroom/innovation/20170807/5-ways-walmart-uses-big-data-to-help-customers)
Walmart has a broad big data ecosystem. The big data ecosystem at Walmart processes multiple Terabytes of new data and petabytes of historical data every day. The analysis covers millions of products and hundreds of millions of customers from different sources. The analytics systems at Walmart analyze close to 100 million keywords on daily basis to optimize the bidding of each keyword. The main objective of leveraging big data at Walmart is to optimize the shopping experience for customers when they are in a Walmart store, browsing the Walmart website, or browsing through mobile devices when they are in motion. Big data solutions at Walmart are developed with the intent of redesigning global websites.
2nd person to respond to Thiago
Hello Professor JP and Classmates
As you think about your company’s ability to forecast future sales and profit, what are two or three of the most significant variables that are difficult to predict?
Indeed, predicting the future is never easy, where assumptions are taken based on historical data, macro/micro economic indicators, regulations, etc. As such, the forecasting has a certain level of uncertainty which can be reduced with proper planning and data management. As far as Halliburton’s forecast is concerned, the main two variables that need continuous updates are inventory and labor, which directly affects the efficiency ratios such as Asset Turnover and Inventory Turnover. That’s why it is critical to review the forecasting periodically.
What information and data would you use to improve the forecast accuracy?
Asset management and the Human Resource departments are constantly scrambling, moving, and managing assets globally to dynamically meet market demand and hire and train new employees to execute the service. Since the oil and gas industry is dynamic, cyclical, and volatile, predicting is a tough challenge. However, any information that affects the price of the barrel of oil is helpful when it comes to forecasting since it directly affects the volume of operations.
How can you go about collecting and leveraging this data?
Honestly, I am unsure how and where the Finance department collects the data. I believe that any source of data: journals, newspapers, TV, websites, social media, etc., would support data collecting to analyze trends and forecast revenue, inventory, and labor. For example, the oil price recently soured, which immediately affected the demand for our service. Thus companies “operators,” to make more profit, decided to drill more wells and increase production, which requires more labor and inventory to increase capacity. Ultimately, companies will never make game-changing decisions only by using hard data. Senior executives should rightly value ‘unstructured data’ gained through conversation with peers, their own experience, and in sampling the views of suppliers, consultants, and customers. However, the opportunities presented by data and analytics will provide a competitive advantage to those who invest in it (1).
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