There is a lot of talk about the economic slowdown and recession. Reports from foreign markets and uncontrolled inflation do not set a positive mood. Experts are raising the alarm and telling us that tougher times are ahead. Whether we agree with their expert opinions or views, it is reasonable to keep looking at the markets and asking questions that will help us secure our business and the people who work for us and continue to grow despite the difficulties.
Lessons learned from the past
We have learned a lot about the crisis in recent years from the pandemic. It has changed our landscape and the way we work. Many commentaries among the public point to Covid-19 as a major factor in the digital transformation of businesses. The transformation, heralded years ago, was supposed to be a revolution but became a slow-crawling machine. If changes in our lifestyles had not happened in 2020, it’s unclear if it would has ever happened.
Companies that have bet on the digitization of their businesses have been less affected by the negative situation that has taken place in the world. However, this is not the first time when technology has helped entrepreneurs during a difficult global time. In 2018 article, Brad Hershbein (of the Upjohn Institute for Employment Research) and Lisa B. Kahn (of the University of Rochester) compared more than 100 million online job postings from 2007-2015 with economic data. They wanted to see how the Great Recession affected the skills employers were looking for. In examining the listings, they found that the cities hardest hit by the recession had a higher demand for high-end technical skills. The increase in demand was partly because, during the recession, companies began investing even more heavily in technology.
Economists say this is because in times of downturn, the opportunity cost of adapting information technology tools and services are lower than in those with a good economy. When the economy is in great shape, companies focus on producing as much as possible. When fewer people are willing to buy what they sell, and operational processes no longer need to be maintained at their maximum efficiency level, these transfers (without dampening sales) some finances, but also energy, into technology-related initiatives.
Focusing on enterprise data
Technology can make a company more transparent, flexible, and efficient. According to Katy George of McKinsey, the first reason to prioritize digital transformation before or during an economic downturn is that analytics can help executives better understand the business, how the recession is affecting it, and where the potential for operational improvements is.
Every business collects and processes data about itself in some way. Understanding and analyzing them can lead to amazing conclusions.
Personally, I think it’s a good idea to rely on data, not on other people’s views or positions. In life, it is hard to meet people who have their own opinions. Either they will be copies of other people’s thoughts, or they will be reluctant to share them because they may be controversial or misunderstood.
Opinions can also be subjective, and we can be led to objectivity by unassailable data. Therefore, it is worth paying attention to them in the first place and drawing conclusions based on them.
At first, it may seem that the company does not collect any relevant information. Still, after deeper analysis, it is not difficult to find even whole “lakes of data“. For example – I had a meeting recently with one of the law firms I was helping to scale the business from a micro firm to a large team. We talked about their problems and advised on structure and work methodologies. At some point, I started asking questions about what kind of data they collect in their organization. At first, the answers were that apart from financial data and that about their customers, they don’t have anything specific. During further conversation and analysis, we came to a conclusion that such information as:
- the total number of cases per year,
- the cases they are currently handling,
- the time they spend on each of them,
- the time they spend sending documents,
- phone calls, etc.
are simply obtainable and visualizable by them. The company’s managers quickly understood that from this simple data alone, we were able to learn a great deal about the company’s condition and potential improvement places. Only this opened their eyes to the fact that the company was collecting other useful information.
I also had multiple meetings with managers of companies that produce physical goods. I told them that we can measure data coming from the production line and, by analyzing it, catch hot spots that, for example, lead to unnecessary downtime or increase the risk of later complaints or failures of the equipment they produce. I also talked about the fact that we can collect data from logistics or even customers’ homes, where they use our solutions (I wrote about the dangers of this issue in an article on the Internet of Behavior). This will give us an almost unlimited source of data for analysis, prediction, and implementation of continuous improvements that will allow us to hit the needs of our audience perfectly. Importantly, having the newest machines in the factory is optional. Internet of Things devices, sensors, and dedicated software ordered from a software house, can come to our aid.
With data, we can also introduce operational excellence programs, maintain production continuity, improve processes, improve customer service and support, or better forecast sales.
Companies that want to leverage data need to focus on consolidating it from various sources, attempting to visualize it, analyze it, and eventually try to monetize it.
Once we have collected massive amounts of information from various sources, it is impossible to analyze them manually. It is then worth taking care of their visualization first. And when there is a lot of data – artificial intelligence and cloud solutions will help us. These solutions will speed up the analysis and synthesis of data, and it will be easier for us to catch what interests us when making an important business decision.
Automate what you can to focus on what’s important
As organizations, we should also focus on “self-funded” projects. This includes the data-driven decision-making but also (importantly) task automation.
Performing the same repetitive tasks in daily work can be shifted to computers. This frees up massive amounts of time among working people and allows them to use their potential where it comes in handy. Employees will have more time to focus on challenging, stimulating, or creative tasks, giving them a chance to impact the organization. All this leads to increased satisfaction with the activities performed.
Automating processes will strive to centralize information, increase transparency, and reduce the need for repetitive communication while promoting transparent information sharing throughout the organization.
It isn’t easy to completely automate tasks or processes in a company, which is why most organizations automate only part of their business processes and combine them with those conducted manually. Some of the most popular include: data reporting, invoice sending, or customer service (e.g., a chatbot that can answer an inquiry, understand the problem, and connect the customer with a solution).
Recruiting also ranks high. Screening candidates during hiring with special tools that search for information on the Internet has already become natural (the question is whether it is ethical) in many companies. It is also possible to automate a section of the process, such as when a candidate moves to the next stage of interviews. Then the automated system will check the availability of specialists, set an appointment, and inform all interested parties. In the simplest case, this integrated using Zapier: form, cash MACHINE system, calendar, and Slack.
Invest in competence and don’t stop testing
From market data and my own experience and observations, it seems that companies that want to implement modern technologies into their businesses often don’t know what steps they should take. A lack of qualified engineers on board (or too few) means that most ideas are still in the realm of planning or have ended up in the freezer. It also happens that companies are at such a point in their development that the necessary implementations and ideas are so numerous and costly that it needs to be clarified what priorities to give to specific needs. In addition, a great deal of uncertainty makes them unsure whether the implemented solutions will be adopted in the organization. Spending money on something that won’t have a measurable impact creates fear and doubt in management. Therefore, in such a case, I am a huge advocate of quickly testing assumptions with the help of people responsible for a given process in the company using simple tools, and only then successively expanding them or recognizing that the idea was a miss.
Assuming that we would like to launch many pilot projects at once, we should consider for which of them it is possible to build Minimally Viable Products (I write more about what such products are in my book, which can be downloaded here). These are applications that, despite their simplicity, bring value from the first day after their launch. We can also try to direct responding people to courses (you can also buy a book or watch materials on YouTube) with low-code and no-code tools (i.e., those that allow you to “clickable” an application). Moving in this direction, we can quickly prototype or automate pieces of processes by less technical people (of course, more complex integration pieces may still require the help of an engineer).
Thanks to rapid implementation, managers or people responsible for the functioning of a given process in a company can check and analyze the sense of the solution within a few days or weeks, test it in a real environment, and in case of success, bet on a dedicated solution created by an experienced team.
Modern technology is not everything. Remember the people as well
In 2017, Raffaell Sadun (from Harvard Business School), Philippe Aghion (from Collège de France), Nicholas Bloom, Brian Lucking (from Stanford) and John Van Reenen (from MIT) examined how organizational structure affects a company’s ability to cope with an economic downturn. The researchers relied heavily on data from the World Management Survey of manufacturers, which included responses to questions about how much autonomy managers have in making investments, introducing new products, making sales and marketing decisions, and hiring employees.
It turned out that organizations delegating decision-making to those closest to the areas of the companies in which they work (in other words, down the hierarchy) were better able to adapt to changing conditions. These companies were much more adventurous in adjusting their product offerings in response to changes in demand and thus more resilient to the crisis.
So, I encourage you to talk to those closest to the areas in question in your organization. Let’s ask them to share how they see the organization and where the hot spots for improvement are. Decentralizing responsibility will give us the comfort of making decisions with expertise.
To the shore
When thinking about challenging times, the best thing we can do is stay calm. Focus on making important business decisions, taking care of people, and working with them to plan and counter potential problems. After all, when coming to an important event, it is better to be already prepared than to dress up in front of everyone else already there. Also, remember that even if there is a crisis or economic downturn, it will be temporary.
