By Damilare Oyetunji
Introduction
It is a statement of fact to say this 21st century has witnessed a lot of innovations and discoveries. Truly, it is a good time to be alive with the numerous technological advancements that have changed the way we live and interact as humans. One of these inventions is the advent of Hydrogen cars. This invention is a big step taken towards the fight against global warming, which will help us preserve our environment. Another one worthy of mention is Genetic engineering, which is the manipulation of the DNA structure of an organism using biotechnology. It has helped the world in medicine and reproduction, and also a very integral part of the way drugs are being produced, helping us to live a healthier life.
I am not a Hydrogen expert nor am I a Genetic engineer and won’t pretend to be one. The invention in the 21st century that is of relevance to this write-up is Artificial Intelligence. Artificial intelligence is evolving to establish connections between humans and technology. In today’s world, robots, toys, and computers follow human orders and respond to needs according to their wishes.
Just as these different beautiful innovations have changed the way we live, similarly, the advent of Covid-19 caused a lot of disruption to the way we work. It has opened our eyes to remote working. It has also forced corporate leaders to look at more objective ways of measuring the performance of employees because remote working has made it possible for a team member to live in Mumbai and work in Calgary, micromanaging employees has been thrown out of the window. The question that this poses is how we continue to meet strategic objectives and ensure organizational performance with this new reality. One of the tools or approaches that answers that question is the Weekly Business Review.
Weekly Business Reviews (WBRs) are a consistent meeting where you and your team can dive into your KPIs every week, ensuring you and your team are always on the same page. Weekly Business Review relies heavily on performance data and its interpretation.
To get the full benefit of this approach, there is a need for the insight derived from the data to be top-notch so the leadership can make informed decisions. This article seeks to explore the opportunity that Artificial Intelligence provides us in conducting Weekly Business Reviews and how we can harness its capabilities.
Weekly Business Review
We can think about Weekly Business Review (WBR) as if it is a process control tool. A process control tool designed to uncover and disseminate the causal structure of a business, so that the leadership of the business can make informed decisions that will enable the growth of the organization.
WBRs are designed to help the organization make decisions with clarity, boost team collaboration, accelerate decision-making, and steer the whole business toward success and growth.
Colin Bryar, former Chief Operating Officer of Amazon implemented WBR in the organization and has been said to have contributed to the growth of Amazon and how it became an industry leader. Following the style of Amazon’s WBR, WBR is designed to answer three major questions:
1. What did our customers experience last week?
2. How did our business do last week?
3. Are we on track to hit targets?
The three questions listed above are the explicit goals that the corporate leadership will discuss during the meeting, and these three questions are what you should ask yourself as you start to put WBR into practice. The order in which these questions are arranged is important. You can consider the first two questions as different ways of asking about the business.
The first question What did our customers experience last week highlights how important it is to know the experience that your customers had so you can know how to treat them better and satisfy them. This helps the leadership to know what features or products the customer values and what they are saying about pricing, the user-friendliness of the feature, speed of issue resolution, etc. It is imperative to ask this question first as the business exists because of the customers and this builds a customer-centric culture.
Building on this foundation is to understand how the business fared the previous week. The question How did our business do last week helps to put figures and numbers to the answers gotten from question one. The experience of the customers will translate to sales figures, numbers of downloads, reviews on the features/products, customer satisfaction scores etc. This puts a perspective on what is being discussed.
The final question just measures performance which ties to the company’s long-term strategy with short-term incentives. This can be used to make performance-based decisions for teams or employees.
Artificial Intelligence and Machine Learning
Machine Learning (ML) is a subset of Artificial Intelligence (AI) and is a fast-growing technology in today’s world. With the help of past data, machine learning can help computers memorize on their own. This technique for taking data inputs and turning them into predictions has enabled tech giants such as Amazon, Apple, Facebook, and Google to dramatically improve their businesses.
Machine learning is used by businesses to identify trends and then forecast what will attract customers, enhance operations, or enhance a product. However, you must first have an understanding of the inputs required for the prediction process, the difficulties in obtaining those inputs, and the function of feedback in helping an algorithm improve its predictions over time before you can develop a strategy based on such predictions.
In machine learning, a prediction is an information output that is produced by feeding in some data and executing an algorithm.
The main problem with any prediction process is that the training data, or the inputs required to begin producing reasonable results, must either be developed (for example, by employing professionals to classify objects) or obtained from already-existing sources (e.g., medical records). Certain types of data are readily obtained from open sources (weather and map data, for example). If customers believe they will profit from providing personal data, they may also voluntarily do so.
Updating training data regularly could present another difficulty. This won’t matter if the fundamental circumstances around the forecast remain unchanged, thus it’s not necessarily a problem.
One of the major components of WBR is data. The process of automation will replace most of the human work soon. The computing devices must match the capabilities of humans. Rather than reviewing this data manually and assigning some set of employees to draw out insights, an algorithm through the use of ML can be harnessed to do it faster and with better accuracy. The next question is how?
How Machine Learning Can Improve Weekly Business Review
• Data Quality: The standard of the data affects how well your algorithm produces results. When a tool examines flawed data, it may produce incorrect results if the data is of low quality or integrity. Thus, cleaning the data before processing it is crucial.
• To ensure a thorough study and support the team in reaching well-informed judgments, machine learning techniques can aid in transforming unstructured data into a format that is readable by computers. It is important to remember that mistakes might be made, and incomplete data can be produced when developers convert unstructured data into a machine-readable format.
• Artificial Intelligence entails building intelligent computers with human-like thought processes and decision-making abilities. The data can be used by the AI systems to create solutions.
