How to digitalize the decisions that matter

Technology is a powerful ally when it comes to improving decision-making processes. The key is to define which decisions should be digitized, based on their impact on the business and their optimization potential. What questions do we need to ask ourselves to automate the right decisions and maximize their value? What are the steps to follow in the digitization process?

The question is no longer whether machines can make decisions, but what decisions do we want them to make. The first question has been answered many times. For example, I could cite a historical date: May 11, 1997. That day, the world chess champion, Garry Kasparov, was defeated for the first time in his life by the Deep Blue program, created by IBM, in just 19 plays.

The defeat of the Russian chess player made clear not only the ability of artificial intelligence to make decisions, but above all, its power of precision: the logic of machines is less likely to fall into certain errors that condition human judgment.

In particular, during the last decades much has been written about biases that lead to systematic and verifiable errors in the results of a decision. Recently, the Nobel laureate and expert in behavioral economics, Daniel Kahneman, published a book in which he introduces the concept of 'noise', in reference to the variability of people's decisions, subject to factors as unpredictable as mood or climate.

None of this affects machines, and it is why they are able to decide with greater precision. The business world has taken due note of this advantage, because it knows very well that a correct decision, made at the right time, can define the success or failure of a business. Hence, the digitalization of decisions is a key pillar of the incredible transformation that organizations are undergoing. In fact, we can think of it as a long process in which companies have been gradually incorporating different tools with which they have been able to evolve from analogical decision making, based on unstructured information and on intuition, to an almost totally digital procedure, in which algorithms or artificial neural networks recommend alternatives and steps to follow. In the most extreme case, an artificial intelligence can be configured to make the decision directly, without human intervention.

This process has accelerated in recent years, having overcome some important barriers such as the low processing capacity of machines, the scarce and insufficient quality of information and data to implement artificial intelligence on a scale, or the natural resistance on the part of clients and industry management agents to abandon less systematic decision-making processes. Since then, the appearance of Big Data and Cloud Computing has multiplied access to information, while Machine Learning and Deep Learning techniques have strengthened their operation; two decisive factors for digitizing decision making.

Identifying decisions that matter

It is becoming more and more evident that a company that decides better, does better. If, in addition, machine intelligence can improve the decision-making process, what follows is to ask: what are the decisions with the greatest potential for digitization and positive impact on the results of a company. In general terms, we can think of a process that includes the following steps:

Listing all impact decisions. The first step is to list all the decisions that have a significant impact on the results of the organization, and choose which of them are worth considering for digitization. Ask yourself: What decisions impact key results? What decisions are addressed in each committee? What decisions are made at each stage of a flowchart? This review exercise is also a good place to diagnose the current state of decision making and identify processes where complexity has become unmanageable, where data is abundant and ideas are scarce, and where there is an opportunity to bring together multiple decision silos. Additionally, starting by listing the decisions prevents us from falling into a very typical mistake: processing and analyzing data, without knowing why we are doing so, without clearly identifying the business objective behind it.

Prioritizing decisions with the highest expected benefit. From the previous list, we are going to select two main types of decisions. On the one hand, those that have great impact on the company's income statement. On the other, it is also convenient to prioritize decisions that are made many times and their recurrence yields an important value (amount per repetition). In both cases, it is necessary to take into account the potential for reducing errors, such as bias or noise. Ask yourself: What impact does the decision have? How many decisions are made per month? Are there errors or noises that could be reduced? In this selection, it is worth considering what other actors in the organization, and even in the ecosystem, the decisions we choose are connected with, as well as the context in which they are made, and the possible synergy between human and artificial intelligence.

Assessing the feasibility of digitizing them today. Fundamentally, it is a question of checking if they are decisions for which we have information and if we are able to structure them, or whether they are decisions that have different alternatives, or are subject to very different risks each time they have to be made. The easier it is to structure decisions and the more information we have, the more sense it will make to digitize them. Ask yourself: Is there recurring information? Is it possible to structure the decision with objectives and predefined business rules? Do you have consistent alternatives and variables? Do we have (or, can we have) the sources of information we need? In this case, it is useful to dwell on each of the components of the decision and assess the extent to which it is possible to create a repeatable approach. Likewise, it is important to put in place initiatives to improve data quality and improve access to internal or external data sources.

Understanding how much it costs to decide. Once the digitizable decisions have been identified, it is necessary to calculate their current cost in time and resources. There are decisions that are very expensive to make and are precisely the ones that are most convenient to digitize. Likewise, we must understand what the cost of strengthening them with technology would be. Ask yourself: What is the cost in time and resources of making these decisions? What is the cost of digitizing them? What is the margin of error they have today? What is the potential of automation? To evaluate the investment in a digitization process, it is also convenient to define how reengineering decision making could move the organization forward; for example, if we plan to drive digital transformation or provide a competitive advantage.

From our experience at Tandem, these steps are very valuable to find the way towards a significant improvement in the quantity, quality and speed with which decisions with impact on the business are made. At this point, having clearly identified the decisions that matter, we are ready to move on to the final stage of your automation: building, testing and putting the right systems into production.

On a day-to-day basis, it is possible to see these implementations in sectors such as mass consumption, which is carrying out a great process of digitization of its marketing process. For example, companies in this sector have a huge number of salespeople who visit points of sale on a daily basis and constantly make decisions to apply discounts or other commercial conditions. Although these decisions have a limited number of alternatives, within certain benefits that can be granted to each client, the final decision is made by sellers and there is a lot of variability when comparing the chosen option to similar situations. For this reason, many leading companies are automating these decisions so that, given certain customer characteristics, the recommendation of the trading condition to apply is through business rules that enhance profit maximization.

The digitization of decisions is only part of the potential of Decision Intelligence in helping companies take advantage of two valuable resources that are more readily available today than ever: access to large volumes of information and powerful processing tools. The board is set and the pieces are ready to move. What will your next move be?

 

Florencia Lasa
Director at Tandem, Soluciones de Decisión.
fl@tandemsd.com