Making better business decisions in the face of global economic pressure

By Richard Cooke, UK business lead, Keepler Data Tech.

  • 8 months ago Posted in

Organisational risk profiles have changed dramatically in recent months. Any hopes that economic conditions would improve as the global pandemic eased were dashed last year as the war in Ukraine led to surging energy prices, commodity prices and general inflation. According to Aviva’s Risk Insights Report 2023, the rush of interconnected challenges that we’re now witnessing - spanning labour shortages to supply chain disruption - are pushing business leaders to the brink, with economic concerns topping the list of boardroom worries. Equally, PwC’s 26th Annual Global CEO Survey reveals that almost three in four CEOs anticipate global economic growth to decline in the coming 12 months, with more than half having already resorted to cost-cutting measures.

In times of financial hardship, it is only natural that businesses go into survival mode: how can we build resilience? Where can we limit spending? These considerations are of course valid, but they must be well-considered.

Even in tough economic periods, budgetary strategies should not undermine operational effectiveness. Yes, organisations are feeling the squeeze, but businesses are not going to save their way to prosperity.

Standing still during times of change could be a recipe for disaster. Recession or not, firms must constantly be looking to realign their offerings with the needs of their customer bases. For this reason, investing to make logical and informed improvements can pay dividends.

Those enterprises that are more perceptive at understanding client spending patterns, adapting to changing needs, and identifying and eliminating bottlenecks in supply chain and production will be more successful in navigating the recession.

We’ve seen evidence of this during the pandemic period, the agility of cosmetics company L’Oreal standing as a prime example.

In the face of lockdowns, the company recognised it needed to move away from beauty products and towards the hygiene and skincare market to cater to shifting demands. And while its performance dropped in 2020, it achieved record revenues and earnings in 2021.

L’Oreal is a standout case of the rewards that can be reaped from identifying shifts and acting on them rapidly, even in tough economic circumstances. It is, therefore, vital that organisations take a similar approach in this latest recessionary period – an approach that must be underpinned by data.

Enhancing data maturity

Now, more than ever, the use of data to support decisions is critical for business. 

Increasingly digitalised companies are seeking ways to boost their margins and reduce costs by improving operational and resource efficiency, optimising time-to-market and enhancing product differentiation.

Using data effectively, organisations can drive towards these goals, unlocking capabilities such as demand forecasting, stock optimisation, and operational automation – priorities we expect to rise to the fore throughout 2023.

To realise these benefits, businesses need to ascertain their level of “Data Maturity” and identify ways to improve data quality, developing more robust and reliable models, and increasing big data competencies to manage increasingly demanding processes.

A critical part of this maturity puzzle lies in the ability of organisations to simplify their data ecosystem using public cloud.

Public cloud made it more cost effective to analyse vast quantities of data in near real-time thanks to improvements in scalability and performance. Equally, it has made it easier to deploy components and ingest data that is reused in multiple instances.

The importance of data products in 2023

With improved data maturity and a sound public cloud architecture in place, firms will be well-positioned to embrace data products.

At present, many are building out multiple unique data projects to improve process automation, optimise resources, and obtain valuable information to improve decision-making.

Each of these projects involves the development of analytical tools such as dashboards, and/or complex ML models that rely on large amounts of data to be effective. Tasked with building these siloed projects, centralised data and ML teams can quickly become bogged down, resulting in project bottlenecks.

To overcome this issue and develop and deploy data projects much more quickly, organisations should instead centre their data strategies around the development of data products.

Data products are reusable assets that provide reliable data for a specific purpose aligned with business needs. Comprising data, public cloud technology, and custom-developed business logic, they provide business users with everything they need to use data to understand and solve a problem.

Unlike data projects, they can be repurposed to support numerous use cases across multiple functions, enabling firms to unlock vital, actionable insights and make smarter decisions at greater speed.

Whether it’s improving understanding of buying behaviour and customer experience preferences, gaining first-mover advantages on product and service trends, or reducing production and supply costs and bottlenecks - data products are vital for firms looking to improve decision-making in the face of global economic pressures.

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