Time to focus on operational efficiency instead of growth at any cost to survive
June 13, 2022
4 min read
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Every week Ihave the opportunity to talk to executives of companies in various industries and sizes and there is now a very clear consensus that an economic crisis is coming. Some even argue that it is already here, given the S&P 500 index is down by 16%, the NASDAQhas dropped 27%, while the DAX has decreased by 11% since the beginning of 2022. These experts agree that we won't see as quick of a recovery as we did during COVID as we have structural issues in the economy that could take quite a long time to resolve. While this article doesn't want to explain every detail on the key drivers behind the economic downturn, I would like to still touch base on the most important reasons. I want to do sobecause this crisis may be different from what we have seen before, and that should influence how executives shall react in this situation.
The current environment causes a huge change of trend in the economy. In the last 10 years growth stood above everything. That was driven by the abundance of capital that could be found on the markets, which eventually was driven by the very low interest rates and the continuous fiscal stimulus (i.e., money printing) that central banks have been doing in order to first recover the economy from the previous crisis and then from the COVID. In these years, for many companies the manifesto was to grow at all cost, burn capital as quickly as possible, and with that increase company valuations for shareholders. We witnessed super high EV/revenue multiples and crazy valuations for companies that have never been profitable. The vast amount of money also resulted in record low levels of unemployment, increasing employee wages significantly, especially in high demand areas.
While these demand-driven trends had already put a high pressure on inflation, supply-driven inflation has also appeared. The COVID induced lockdowns had already created shortages in various industries, from chips via steel to paper. Then the Ukranian war broke out and limited the export of several additional critical items such as oil, gas, wheet or barley. The combination of demand-driven and supply-driven effects increased inflation to levels that haven't been seen for decades. That led to a moment when central banks had no choice but to increase interest rates again, after many years. With increasing interest rates, capital is not cheap anymore. Financing growth got significantly more expensive as private investors don't see that attractive of a return anymore in companies not generating profit, and as the interest rates of loans or bonds have also become more expensive thanks to the increasing base interest rates.
Of course the above mentioned story is overly simplified, but it still shows why growth above all cost will not be a winning strategy in the coming years. Instead, the main theme of the next years will be profitability. Investors have already started valuing industries and companies with healthy profitability higher, for instance value stocks performed much better than growth stocks in the first half year of 2022.
With profitability in the focus, operational efficiency will not be a secondary aspect anymore, but a key to survival. The good news is that there are many levers to pull, given lots of corporations deprioritised this area during the period of growth. The first signs of this phenomenon are already visible, such as the hiring freezes or layoffs that are already happening, especially among fast growth tech companies (though still trending at lower levels than during COVID):
For instance, Coinbase, Lyft, Meta, Nextflix or Uber all announced hiring freezes or slowed down recruitment in the previous months. There have also been significant layoff plans communicated or already executed at the following otherwise fast growing & popular companies according to Layoffs.fyi:
Luckily, layoffs are not the only way to improve operational efficiency. The good news is that we have seen amazing technological improvements in the last 10 years that we can now utilise to achieve significant operational improvements.
For example, thanks to all the digitalisation that happened in the past years across all industries (either on the hardware/IoT or on the software side), companies have vast amount of data about their operations. Sensors are collecting data 24/7 from manufacturing sites, from the transporting vehicles delivering the products or from the stores where they are sold to end customers. Many of the customer journeys are now moved to digital channels, from comparing products or services, via purchasing them to managing aftercare online. Technology improved to transfer more data faster and at lower latency than before, for instance thanks to 5G.
All these petabytes of data is getting collected more and more frequently in cloud based data sources (e.g., Google BigQuery, Amazon Redshift, Snowflake), making them easily available to all stakeholders (with access). There are more and more tools that transform, clean and complete the data (e.g., Airbyte, Fivetran, dbt), making it available for previously unimaginable amount of use cases.
Probably the simplest use case is to visualise data on dashboards (e.g., in Tableau or Looker) to facilitate the decisions of the different stakeholders in the company. You can for instance present the most important KPIs that you identified after drawing your KPI tree based on my previous article.
Another use case is to build analytics layers on top of the data, and establish data analyst or data scientist teams that understand patterns and behaviours based on large data sets. That practice can start with simple Excel- or Looker-based analyses and move towards applying really complicated predictive analytics or sentiment analyses. My experience shows that if someone generates the right hypotheses for these analyses, tremendous amount of impact can be created from the generated insights.
Last but least, nowadays companies can build sophisticated automations on top of the their collected data. Automations can be as simple as workflows based on triggered events such as automated emails or Slack messages. But automations include robotic process automations (RPAs) for repetitive, simple business processes or even robotisation with the help of machine learning & artificial intelligence in factories or behind the driving wheels of trucks.
As an ex-consultant I know that achieving operational efficiency requires a combination of various factors: a compelling north star vision from the leadership, a great company culture, clear processes etcetera. However, I also truly believe that technology, and within that, data will play THE key role in improving operational performance in the following years. Companies that can truly harness the power of technology will be able to create lasting competitive advantage with improved profitability and thus ultimately better customer experience, and those that cannot do that will drop behind eventually.
If you haven't put profitability and operational efficiency improvements on top of your agenda yet, you should do it NOW to survive the upcoming economic downturn. Companies that react too late will have much less runway to navigate and will need to take much more radical steps.
To end on a positive note, this is, however, also an opportunity for many companies. As Ayrton Senna once said:
You cannot overtake 15 cars in a sunny weather... but you can when it's raining.
What do you think of the ideas shared in the article? Please feel free to comment your thoughts or questions in the topic or share the article with your colleagues / friends.
Also, please feel free to reach out to me if you want to discuss how technology can help improve operational efficiency. I'm happy to talk to likeminded professionals in this topic.
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