The Decision-Making Process at Amazon

The actions and attitudes of individuals and groups within a firm form a basis for understanding organisational dynamics. One of the most important executive processes in this regard is decision-making. Besides impacting every corporate level, managerial decisions affect problem-solving and group processes within the organisation. Technological advancements and streamlined business processes in the modern world have made the role of decision-making even more critical. The implication of this is that individuals within an organisation have to make fast and accurate decisions in their daily work activities. Amazon.com, Inc. is one of the world’s largest organisations. Besides its commercial success, it is renowned for its streamlined operations which translate to proper decision-making. This paper will, therefore, analyse the decision-making processes within Amazon and how they influence operational effectiveness. The insight derived from the analysis will help inform recommendations on how decision-making at Amazon could be improved.

Company Profile

Amazon.com, Inc. is an e-commerce giant whose business traverses a range of product categories and services. The company has three segments: “North America, International, and Amazon Web Services” (Reuters.com). The corporation’s business model entails providing a merchandising platform for sellers. Additionally, it diversified into the world of consumer electronics with offerings such as Alexa speakers and Kindle tablets and e-book readers (Amazon, N.d.). Online retail forms the bulk of the organisation’s operations and has, in essence, made the company the household name it is today. The Amazon Web Services segment, on the other hand, consists of the sale of cloud services for start-ups, companies, and government institutions.

Amazon’s success is attributed to a variety of factors which are vital in this context since they help one understand the organisational dynamics. The company’s progressive mindset has led to the development of innovative technologies and practices that have helped distinguish Amazon from its peers. The commitment to world-class customer service has also helped the institution to gain a loyal client base. The simplicity and convenience associated with the various customer-oriented tools have helped enrich the online shopping experience.

Decision-Making Processes at Amazon

Theoretical Framework

Decision-making processes in large organisations are complex due to the multiple variables involved. Such complexities apply to Amazon especially considering its aggressive growth strategy in the past decade. CEO Jeff Bezos’ approach is the foundation of the company’s decision-making process. According to Bezos, decisions in the organisational setting are categorised as either Type I or Type II (Rosoff, 2016). The former involves strategic choices which are characteristically consequential. Such decisions include pursuing new markets and product lines, downsizing, and acquisitions. The arrangements set the course of the organisation and are usually made by executive-level management (Shivakumar, 2014). Type I decisions should be made carefully and methodically since they are irreversible. However, most choices in an organisation are not Type I since they are reversible. Bezos refers to these decisions as Type II, and they can be made quickly by individuals with good judgment or relevant experience. This categorisation points to tactical and operational decisions. The decision-making process in the case of Type II determinations is relatively fast as compared to the systematic approach adopted in Type I decision-making.

As organisations grow, most adopt the methodical Type I decision-making process in most situations, including those that are tactical and operational (Goffee and Scase, 2015). This approach leads to slow decision-making within the organisation. In addition, it leads to unthoughtful avoidance of risk, failure to experiment sufficiently, and as a result reduces invention (Pettigrew, 2014). The rule followed within the organisation is that most decisions should be made when the individual in question has approximately 70 percent of the information they wish they had. The rationale behind this rule is that if a decision-maker waits to get 90 percent of the information, they will probably be too slow (Rodriguez et al., 2016).

Decision making at Amazon is a collaborative process, especially regarding tactical and operational decisions. Multiple points of view are considered since they ultimately improve decision-making. However, there are frequent disagreements in such situations, and this could significantly delay decision-making processes. The resultant problem contradicts the high-velocity decision-making model that the organisation follows. To rectify this anomaly, Amazon also follows a tenet referred to as ”disagree and commit” (Amazon, N.d.). The principle concedes that consensus is not always possible in an organisational set-up.

Operating Agreements

The discussed principles form the basis of decision-making processes throughout all segments of Amazon. A closer look at the critical components of the high-velocity decision-making model reveals how individuals and teams would function and interact within the confines of the organisation. Cross-functional decision-making at Amazon is the responsibility of the executive leadership team. The decisions involved at this level are Type I, and are handled at executive meetings. The issue requiring deliberation is presented to the executive team as a proposal. With PowerPoint presentations banned by Bezos, the proposal is presented in a standard six-page, narratively-structured memo which all executives must read before the discussion begins. The paper outlines the reasoning and approach, asks and answers tough questions, and explores alternative considerations. This culture leads to high-quality executive discussions because all involved parties gain a better understanding of the relevant issues. The deliberation at this stage is thorough hence leading to better strategic decisions. Quality and speedy execution are also prevalent in Amazon’s Type II decision-making processes. The existing culture at the organisation emphasises the importance of gathering data and seeking upstream and downstream perspectives before making a decision (Amazon, n.d.).

Despite the differences between the Type I and Type II decision-making processes, there is a common underlying theme across the two. Amazon commits to ensuring the honest discussion of facts before decision-making. The spirit of cooperation is evident throughout the organisation. However, the company maintains a bias for action especially when it comes to Type II decisions. In this case, calculated risk-taking is allowed with sufficient but not necessarily extensive study. The latter is reserved for Type I decisions which are made by the executive team (Hoefer and Green Jr, 2016).

The Application of Decision-Making Models at Amazon

Decision-making techniques are designed to help leaders and managers make effective non-programmed decisions. Any such framework is meant to maximise the quality of related outcomes. The nature of the implicated situation influences the decision-making processes at Amazon hence the variance between Type I and Type II decision-making processes. An evaluation of the mechanics of the processes reveals a combination of several decision-making models at Amazon. Multi-method approach enhances flexibility in decision-making which is lost when an organisation opts to use one model exclusively (Kandemir and Acur, 2012). Accordingly, this section will review the use of three models- rational, intuitive, and creative- in Amazon’s operations.

Rational Decision-Making Model

The rational approach is a classic framework that describes a series of linear steps that guide decision-making processes. The rational process has a bias for logic, objectivity, and deep analysis. Consequently, there is a reduced emphasis on aspects such as insight and subjectivity (Byrnes, 2013). The model is characteristic of the Type II decision-making at Amazon which includes operational and tactical decisions. The first step in this model is the identification of the problem. Managers provide their input by defining the gap between the current state and the optimal or desired state of the organisation. The second step is identifying the criteria that will be used to solve the problem. The criteria act as a guide throughout the decision-making process. This step is unique to each issue and as such context is vital. The third step of the rational model involves weighing the established criteria. Each criterion has its level of importance to the organisation. Therefore, comparing the various criteria would help provide significant insight for the decision makers (Baumann et al., 2014). The fourth step in the linear process is generating a list of alternatives. This stage revolves around brainstorming, and substantial stakeholder engagement is necessary. The next step involves evaluating the alternatives identified in the previous step. The number of criteria determines how long the step will last. Evaluation could be done using a basic rank-order method where each option is evaluated according to the set criteria. The sixth step involves ascertaining the optimal decision. This determination is based on an evaluation of the ranking analysis. With each criterion having a different level of importance, one can assign more influence to results in classes that have more importance (Velu and Stiles, 2013).

Evaluation of how Amazon uses the rational decision model

According to an interview documented by Business Insider, Jeff Bezos believes that some choices need to follow the rational decision model (McGinn 2018, p.1). Based on the approach; Jeff Bezos has adopted a near-zealous deference to data as the base for operational and strategic decision making (McGinn 2018, p.1). Firstly, the company rigorously collects data and analyses the on-going efforts to improve customer service. Thereafter, the business tracks key performance indicators and relates them to consumer experience. All business processes are then analysed aggressively. Some of the parameters evaluated include human resources, financial evaluation and web development. For instance, the enterprise gives its employees the power to independently examine measure, analyse and assess data related to work of the company (Holland, & Matthews 2018, p.9). Thus, the idea is to encourage staff to explore hidden insights and such data can be used to rationally make decisions. Decisions are reached through analysis rather than a top-down approach. Principally, the CEO contends that the input of low-level employees is just as important as that of senior-level executives. The reason for adopting such a decision model approach is to encourage insightful and creative members of the company to make necessary contributions to serve the consumers. More importantly, the CEO notes that data-driven management creates a rationale whereby facts overcome rank, and thus inner-office politics would be a thing of the past.

Douglas Gurr, the head of Amazon UK notes that the company first measures its productivity and profitability in terms of metrics such as revenue and customer growth. Specifically, the CEO notes that the degree at which clients continue to purchase on a repeat basis is what defines whether the business is growing or regressing (McGinn 2018, p.3). In the 2018 shareholder letter, Bezos notes that the company measures programs and investments analytically. Thus, the organisation gets rid of those operations without acceptable returns and improves investments that work best for the institution.

When launching a new fulfilment centre at Houston, the institution evaluated the product mix, dimensions and weight, and, used those parameters to decide the space and facilities that were required. To shorten delivery time, the company analyses forthcoming locations based on contiguity, transportation hubs and standing facilities (Holland, & Matthews 2018, p.4). Additionally, decisions on inventory purchase are numerically modelled and thus, they are able to deliver enough inventory thus saving associated holding costs. For instance, the model uses qualitative analysis of historic purchase data to predict consumer demand and changeability. Data on vendor performance is analysed to determine stock-replacement times. Within the fulfilment network, the corporation determines and where to stock the product based on inbound-outbound customer locations and shipping costs.

Intuitive Decision-Making Model

The intuitive model was born over the realisation that it is not always possible to follow the long and linear steps that define rational decision-making. This impasse is particularly important to critical calculated decisions. The model appreciates that managers often make decisions under challenging conditions (Klein, 2015). Another consideration by the model is that managers rarely make decisions that are entirely based on data (Dreyfus, 2014). The intuitive decision-making model emphasises proper judgement and the use of knowledge based on experience. Experts and seasoned leaders make decisions using this model by scanning the environment for cues to recognise patterns. When the decision maker recognises a trend, he or she can suggest a possible solution based on their prior experience. Decisions made in this manner are usually successful since the decision maker has an idea of their effectiveness. If they deem a potential solution as not workable, they work out alternative solutions.

In a recent interview published at the company’s shareholder’s letter, Jeff Bezos, CEO of Amazon discussed how he makes great decisions using the intuitive model. He argues that he never uses a one-size fill decision model. Essentially, decisions that he makes have to be reversible and, they should be able to use a light-weight process. Jeff Bezos argues that most decisions that he makes as a CEO are typically based on 70 percent of the information that he has because if he waits for full information, then it would be of no good because the opportunity would have passed (McGinn 2018, p.3). Using the intuitive model he recognizes and correct bad decisions. The CEO notes that most decisions are not life and death and they can be easily reversed with little pain. Additionally, the intuitive model applies to Type I decision-making at Amazon. The executive leadership has to make quality strategic decisions while still ensuring that they are not too slow in the process. The approach adopted by Bezos is combining a data-driven approach with intuitive skills (Sisney, 2018)

Creative Decision Making

Besides, the rational approach and the experience-driven approach, creativity is also an important part of effective decision making. The creative model involves generating new and imaginative ideas to solve problems within an organisation. The model is the result of the flattening of systems and intense competitive both within firms and in the market (Proctor, 2010). Problem identification is the first step of the model as is the case with other alternatives. The second stage is referred to as immersion, and it involves the decision maker thinking about the impending issue consciously and gathering necessary information. The central factor in creative decision making is having expertise in the relevant field. The third step in the process is incubation where the decision maker moves away from the problem and does not think about it for some time. During this stage, the brain is deliberating on the problem subconsciously (Čančer and Mulej, 2013). The fourth step, illumination, involves the individual in question having an insight into the solution when it is least expected. Finally, the verification and application stage pertains the evaluation of the solution to determine its feasibility before implementing it within the organisation (Amabile and Pratt, 2016).

In a published interview obtained from the Harvard Business Review, Rick Dalzell the Senior Vice President of Amazon was asked what kind of decision-making model drives the growth of the enterprises (Hansen 2018, p.2). He argues that the company does not accept conventional wisdom about the way operations are typically carried out. Thus, the organisation reinvents everything, including small things that most companies assume. For example, during the launch of the Kindle Fire Tablets, most tech companies would hold big conferences. Instead of doing so, the CEO brought a few reporters in to see him in small groups and he did the demos himself. Principally, every reporter left feeling like they had a productive and special session with Jeff Bezos (Hansen 2018, p.3). Consequently, the reporters passionately covered the sessions and the company received excellent press coverage due to the creativity. Creative decision-making has made Amazon the company it is today. Another example is the futuristic decision by Bezos on starting an online bookstore redesigned how people purchased and read books. The creative paradigm shift was based on Bezos’ philosophy to create rather than predict the future (Popomaronis, 2018). The idea was actualised, and the company diversified to virtually every retail category. The creative decision-making process is also evident in its customer service. Amazon is continuously committed to improving customer experience through innovative technologies. The Amazon Prime membership program, for example, successfully challenged existing notions on the online retail experience.

Factors that Influence Decision-Making Processes at Amazon

Amazon’s success can be attributed partially to its efficient decision-making philosophy. The platform has enabled managers to act swiftly to solve urgent issues without compromising the quality of the final decision. However, there is a variety of challenges that undermine proper decision-making at the organisation. A review of the challenges will provide the context for suggestions for improvements.

To begin with, one challenge that impact of decision making is the overreliance on one decision model compared to another. In making some costing decisions, the CEO relies on an intuitive approach rather than a rational-based method (Holland, & Matthews 2018, p.10). In Amazon’s context, there has been a problem of increasing operating costs over the past five years due to the company’s diversified growth. When formulating decision criteria to solve this problem, considering factors such as time and cost is necessary. Amazon’s operating costs problem is significant since it affects the organisation’s financial performance. The graph below shows Amazon’s cost-revenue function.

Chart 1: Amazon’s shipping revenue compared to cost

Source: Holland, & Matthews, 2018

The chart compares Amazon’s shipping cost and revenue between 2006 and 2016. The analysis shows that the costs have been rising faster the revenues. For instance, the shipping costs are more than 15 billion USD while the respective revenues were less than 10 billion USD in 2016. By using a mix of intuitive and rationale decision technique, the company can use such data to reduce costs and still be able to diversify. Possible alternatives to shipping include outsourcing, hardware manufacturing, increasing the number of warehouses to reduce transportation costs, and automating warehouse operations. Warehouse automation, for example, would significantly reduce labour costs and implementation would involve sourcing suppliers for automated systems and redesigning warehouse operations.

Another challenge is information inputs. Individuals must have the right information to support the decisions they make. The quality of the decision suffers if the information provided is not adequate and accurate (Romiszowski, 2016). At Amazon, the chief executive developed the 70 percent rule to cater for the inconsistencies of knowledge management and facilitate faster decision-making. While little information is dangerous, too much could also be problematic (Rodríguez et al., 2016). The reason behind this is that it limits the scope for intuitive decision-making which is important especially for Type I decisions. The problem was evident throughout the life of the fateful Amazon Fire phone. The company’s decision makers were fixated with cramming innovative features into the phone and ended up compromising the overall consumer experience. Amazon failed to focus on the basics of convenience and usability which have served the company well since its inception.

Prejudice and bias are also relevant issues in the case of Amazon. Perceptual processes significantly influence decision-making, and this could lead to ineffective decisions (Ferrell and Fraedich, 2015). Individuals within an organisation will view things differently, and that is expected. However, it could lead to slow decision-making and discontent within the organisation. The disagree and commit policy rectifies the issue of speed, but it doesn’t deal with the discontent that ensues. The problem is heightened by the diversity of the organisation’s operations which introduces a bias towards an individual’s department. The implication is competition within the organisation which could eventually harm the corporation’s culture (Hogan and Coote, 2014).

Recommendations

Amazon’s decision-making philosophy has served it well over its years of existence. However, some improvements could be made to optimise the quality of decisions. The first recommendation is to invest in proper knowledge management systems to help provide relevant information to decision makers promptly. The right tools would prevent the effects of information overload which is costly. A system that provides centralised oversight and control would be the best solution for an organisation as diverse as Amazon. The second recommendation is for the company to deal with subjective inclinations better. The disagree and commit principle should also include provisions on how to handle the differing opinions rather than just ignoring them. The processes would ensure that discontent does not increase within the organisation.

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