Demand Forecasting Term Paper
Demand planning and forecasting is an important step in ensuring that companies are able to meet the demands of their customers with the right products, at the right time. With an increased number of options available, customers are demanding efficiency from companies in return for their loyalty. With a rise in competition, efficient demand planning and forecasting has become the new frontier in which companies are waging wars against their competitors. Giving customers a good experience while keeping the costs low is every company’s goal, as this helps in managing operational costs while serving the needs of customers efficiently. Thus, demand planning and forecasting is crucial in the modern world of business where competition is high and consumers are demanding efficiency in addition to other product qualities.
Consumer Packaged Goods Industry Challenges
The consumer-packaged goods industry is a sector which deals with first-moving-consumer products as they are used up quickly and need to be replaced regularly. The sector faces the constant need of ensuring that the products needed by customers are available on demand. The products are low-cost and companies make small margins per product. Thus, the profits made are based on the ability to sell the products in bulk, which means that efficiency in demand forecasting and planning is required to meet the demands of customers as the need arises.
Challenge 1: Stiff Competition
The consumer-packaged goods industry is a lucrative sector due to the ease of market entry and the ready market for the kind of products sold. Moreover, the profit margins are large, due to the ability to sell the products in large quantities. According to studies, Amazon, one of the largest online retail stores constantly faces stiff competition from other players in the market. Despite a heavy investment in technology and infrastructure, the ease of entry in the online retail sector presents new competitors for Amazon, regularly (Hübner, Johannes, & Andreas 567). For example, most brick and mortar companies now have online stores through which they sell their products directly to consumers while small enterprises can now easily sell their products directly to consumers by interacting with them on platforms such as social media. In addition to small, local businesses, Amazon also faces competition from international online retailers such as Alibaba, which also operate internationally, thanks to the ease of logistics and increased internet penetration across the globe. According to studies, Walmart, the largest retailer, still commands a 3.7% market share while Macy’s a leading online retailer has a 1.2% market share (Hübner, Johannes, and Andreas 567). Thus, competition is not just from small, local firms, but also from international players. With demand planning and forecasting, companies can fight off competition by ensuring that they have the right products as required by customers, and at the right time. This will stop customers from going to the competition. In the packaged goods sector, this is critical as it reduces the chances of consumers going to online shops, which have proven to be more efficient over time.
Challenge 2: Increased Demands from Consumers
Today’s consumer lives in a fast-paced world, where there are many options available to them on demand. This has created a sense of urgency, which companies must adapt to, if they would like to stay competitive and in the market. This has forced companies to be innovative, to enable them deliver products on demand. Amazon is a market leader in this kind of model, aimed at meeting the needs of consumers on demand (Tolstoy, Anna, and Dharam 297). However, many online stores are facing a problem, as they have to organize logistics to deliver products and this sometimes takes a few hours to a few days. Amazon has invested in modern technology, with the use of drones being touted as the latest effort towards meeting the needs of customers on demand. The rise in demand by customers, from quick delivery to the availability to options based on their needs is a challenge to many companies which do not have the financial ability to invest in heavy technology to meet these needs (Hübner, Johannes, and Andreas 574). This has partly been the reason for Amazon’s dominance in the online retail sector, as it also owns most of the technology required to facilitate the quick delivery of products to customers on demand. Despite these capabilities, is still faces the challenge of meeting the needs of its customers adequately, since the demands keep increasing and, in some cases, meeting all the demands may lead to an increase in overheads. Studies have indicated that about 55% of online retail searches start with Amazon, which shows that the increased dependence on the fast, free model by the company is placing pressure on it to meet the ever-increasing demands of customers (Tolstoy, Anna, and Dharam 302). This is related to demand forecasting and planning in that customer needs keep changing and this can affect how the company executes its plans, based on forecasts.
Challenge 3: Too Much Data and Poor Analysis
The modern era is known as the era of big data. The amount of data available to companies is a lot, courtesy of improved technologies, which help in the collection of data on customer needs, behaviors, trends, and tastes. The data, however, is often in its raw form and requires careful analysis and interpretation, to make business sense. The problem of big data was brought forth by the availability of improved technologies which helped companies turn customer interactions into data and the advent of companies that specialize in data mining (Tolstoy, Anna, & Dharam 309). However, the process of analysis is based on the needs of the specific industry as well as those of the specific company, and this can be a challenge due to the amount of data available. Amazon is one of the companies with the largest amount of data in the online retail sector, due to the use of modern technology and the fact that it owns platforms customized to its needs. This has played an important role in helping the company make critical decisions which have helped it meet some of the demands of its customers. However, just like smaller online retail companies, the company faces the challenge of making sense of all the data collected and connecting it to business goals (Hortaçsu & Chad 93). Smaller companies also face the challenge of analyzing the data they collect, to help them in demand forecasting and planning. Due to the changes in the market, online retailers have to contend with a lot of data types that they have to deal with, with the main 4 being consumer behavior, demand forecasting, targeted promotion, and dynamic pricing (Schu, Dirk, and Bernhard 738). Thus, while data is important in demand forecasting and planning, the availability of too much data presents a problem if poor analysis is done.
Challenge 4: Lack of Market Standards
The online retail sector is a relatively new sector which caters to a different set of clients than what was being handled by brick and mortar companies such as Walmart. The rise in technology and internet penetration in the past 20 years has seen a revolution in the sector, which has surpassed the formulation of policies and standards to govern the operations of the sector. Predictably, the big players, such as Amazon, are the shapers of the sector and the determinants of market standards (Schu, Dirk, & Bernhard 740). However, this locks out smaller players who do not have the same capabilities. Moreover, the lack of standards makes it hard for Amazon, the market leader to determine how it should structure its model of operations for maximum efficiency. This is because, it has to invest in its own research and development, which is something that can be easily resolved if there are market standards set in place. Thus, the delay by policy makers to take lead in research and development has increased operating costs for companies, which undertake this burden and push the cost onto consumers, leading to a slow uptake of the services provided (Shi et al 155). The problem of poor market standards was caused by the rapid growth of online retail while the necessary policy makers did not have the capacity to study and device appropriate standards, with the ones being used at the moment being those that were used by traditional brick and mortar retail stores.
2. Technologies Being Used
Demand forecasting and planning has always been a part of the retail sector, especially the consumer-packaged goods industry. With the advent of technology and the need to meet customer needs, even faster than before, the player in the industry have had to adopt technology to help them in collecting and analyzing relevant data which provides real-time information that can be used to make accurate decisions. Thus, the use of technology has been pivotal in promoting demand forecasting and planning.
Technology 1: Customer Service Platforms
The need to collect data on the needs of customers and trends in consumer behavior has necessitated the rise of customer service platforms which collect data every time consumers interact with online retail platforms. This data mining platforms, are critical in demand forecasting and planning so as to meet the increased number of customer demands. This is because, data is collected and analyzed in real time, which provides platforms such as Amazon with refined data that can be used to make decisions (Hortaçsu & Chad 98). The data gathered and analyzed is further used to fight off competition, since the company has refined, actionable data that is used to make decisions. For example, Amazon has been using customer data to determine where to have warehouses so as to serve customers faster. This is based on the data gathered about the most commonly demanded goods in certain regions and the demand levels of the regions, which facilitated the opening up of warehouses to help in the quick delivery of products (Hortaçsu & Chad 98). Another advantage is that the customer services platforms work 2-way, in which it is possible to track the progress of a customer’s order from the beginning to the end which increases transparency and customer trust, an important factor in fighting off the competition.
Technology 2: Industry Analytics Tools
With the availability of data online, and the dominance of search engine platforms, it is possible to use technology to gather data about the performance of certain industry. With improvement in technology, it is even now possible to get data on the activities of competitors with metrics such as website visits, and the kind of users of certain websites now being readily available (Popescu 102). This has been instrumental in helping companies know who their biggest competitors are and then devise ways to compete with them. For example, Amazon can easily access data on the kind of user who are on Macy’s and Alibaba and then use this data to determine what methods are used by the two companies to attract the customer segments. This was the rationale in starting same day deliveries at no cost, as Amazon realized that brick and mortar stores were popular due to the ability to meet the needs of customers at the right time. The company realized that being closer to the customer was helpful in winning the trust of customers and thus, beating off competition (Shi et al 150). Industry analytics tools were proven to be essential in knowing what the current trends in the market are. This is because, trends change and what works in one company can easily be adopted to improve the delivery of services to other clients.
Technology 4: Data Analytics Platforms
The collection of data is not enough to help in demand planning and forecasting. The data collected needs to be analyzed and refined, to make sense to the company such that business decisions can be made based on this data. Previously, data analytics involved complex calculations which were time-consuming and prone to human error. With the advent of data analytics platforms, the data gathered is not analyzed in real time and provided in a simple form that only requires end users to interpret what trends are in the market. The platforms aggregate data from different sources and then calculate it in real time (Schu, Dirk, & Bernhard 749). Moreover, they allow for the storage of data, which can facilitate the comparison of data sets to identify trends and make decisions accurately. Amazon has been known to use data analytics to overcome the challenge of having too much data ta hand and no real use for it. This has been instrumental in keeping it ahead of its competitors. Online retail sectors rely a lot on the collection and analysis of data and the availability of big data has been a challenge, as the use of the data to make decisions was not possible with raw data (Popescu 104). The use of the data analytics platforms has been helpful in demand planning and forecasting, a trend in consumer needs and demand patterns can be discerned and the appropriate measures put in place to meet the demands (Zhang, Pengyu, and Yanmei 108). The use of data analytics platforms was proven to be effective as it helped the companies come up with real time solutions to problems. Additionally, it helped the companies improve their demand planning and forecasting strategy and how it engaged its clients, an important factor in fighting off competition. This can be applied in other sectors, where the needs and behavior of consumers is not clear, to help in determining which paths are most suitable to take.
Technology 4: Online Surveys of Customer Needs and Intentions
While the availability of data collection and analysis platforms has made it possible for online retail companies to gather and analyze data, sometimes the data is not enough as it does not provide insights on the needs of customers as well as their intentions. Moreover, the platforms do not provide specific data related to the needs of the company and its clients (Zhang, Pengyu, & Yanmei 108). As a result, the companies now use data collection platforms which allow them to issue out questionnaires to clients. This has been instrumental in collecting highly relevant data that can be used to make business decisions based on the needs of the customers (Popescu 106). Moreover, companies can collect data based on changes they would like to make or changes that have been implemented, to help them determine whether they are meeting the needs of the customers. One of the key strategies used by online retail companies is that ability to customize services to the specific needs of the customer (Stojković, Stipe, & Zoran 209). This has been helpful in making them user-centric and gain popularity. The most user-centric companies have used online surveys to collect data on customer intentions and sentiments and used this data to improve their products to meet the needs of customers.
In this case, a survey was conducted to determine whether customers preferred to receive their products a day after ordering at no cost or on the same day, at a small fee. The survey was issued out using the company’s social media pages as well as the website. The data was gathered for a period of 1 month to collect enough data to help in making the right decisions. To ensure that the company was aware of customer intentions, the questions were segmented based on the various categories on the site. The data was then gathered, aggregated, and analyzed. It emerged that customers did not mind same day delivery at a small fee. Majority of the customers cited that they preferred using online platforms as they are easy to use and convenient, which saves them the time to go to an actual shop. The result is that the company implemented this strategy, which resulted in higher customer satisfaction and the improvement in the categories of products that were fast-moving products. The same can be applied in another sector, to determine how customers would like the delivery of goods and services. This can be helpful in determining how customers would like to interact with the company and what they considered a priority.
The trend, it emerged was the use of data and technology to improve the experience of the customer. The data gathered indicated consumer trends and preferences and this information is then used in demand planning and forecasting so as to meet the needs of clients adequately. The trend is to now use big data to inform the decisions that a company makes, since this is an accurate way of helping it determine consumer needs (Stojković, Stipe, and Zoran 210). According to the study, companies which use data and technology have been able to customize their services to meet the needs of their clients. This has been helped by the penetration of technology, which collects data any time a client interacts with an online retail store, without requiring the input of the customers.
Hübner, Alexander, Johannes Wollenburg, and Andreas Holzapfel. “Retail Logistics in the Transition from Multi-Channel to Omni-Channel.” International Journal of Physical Distribution & Logistics Management vol 46.6/7, 2016, p. 562-583.
Hortaçsu, Ali, and Chad Syverson. “The Ongoing Evolution of US Retail: A Format Tug-Of-War.” Journal of Economic Perspectives vol 29, n.o 4, 2015, p. 89-112.
Popescu, Gheorghe H. “The Competitive Nature and Effectiveness of Online Retailing.” Psychosociological Issues in Human Resource Management vol 3, n.o 1, 2015, p. 101-106.
Schu, Matthias, Dirk Morschett, and Bernhard Swoboda. “Internationalization Speed of Online Retailers: A Resource-Based Perspective on the Influence Factors.” Management International Review vol 56, n.o 5, 2016, p. 733-757.
Stojković, Dragan, Stipe Lovreta, and Zoran Bogetić. “Multichannel Strategy-The Dominant Approach In Modern Retailing.” Ekonomski Anali/Economic Annals 61.209 (2016).
Shi, Yuying, et al. “The Impact of Retail Format Diversification on Retailers’ Financial Performance.” Journal of the Academy of Marketing Science vol 46, n.o 1, 2018, p. 147-167.
Tolstoy, Daniel, Anna Jonsson, and Dharam Deo Sharma. “The Influence of a Retail Firm’s Geographic Scope of Operations on its International Online Sales.” International Journal of Electronic Commerce vol 20, n.o 3, 2016, p. 293-318.
Zhang, Danlei, Pengyu Zhu, and Yanmei Ye. “The Effects of E-commerce on the demand for Commercial Real Estate.” Cities vol 51, 2016, p. 106-120.