Too big to fail? Why established enterprises need to become digitally agile

By Andrew Hayden, Automation Expert at Winshuttle.

  • 2 years ago Posted in

Established enterprises face the imminent threat of shortened life expectancy, with business consultants Innosight claiming three quarters of companies currently quoted on the Standard and Poor (S&P) stock market index will have disappeared by 2027. While concerns of market instability have been rife over the past few decades, the impact of the Covid-19 has put tremendous strain on household brands to improve operations and become more responsive to survive. Put simply, it’s no longer enough to rely on the ‘too big to fail’ principle. Yet, many large organisations still rely on slow, manual processes to manage their data, hindering their ability to adapt their business models, and become more agile. In an era where effective data management and process automation is at the core of digital transformation, maintaining the old ways is extremely risky.

Built to collapse

Over the past year, there has been a growing list of retail empires that have either disappeared or been acquired by eCommerce companies. Take multi-national retailer, Debenhams, as one example. Founded in 1778, this network of department stores has been part of the British high street for two centuries. After struggling for over a decade with dwindling profits and unmanageable debts, the chain was taken over in January (2021) by 15-year-old online retailer, Boohoo. But, where did it all go wrong? According to the BBC, it became irrelevant by failing to differentiate itself from dynamic new brands and it did not adapt quickly enough as more and more consumers choose to buy online. The decision to open new stores at a time when buying behaviour had shifted also made it difficult for the business to perform, especially given the uncertainty caused by the combination of Brexit and the pandemic. For many organisations that have been forced into administration recently, Covid-19 has just highlighted an underlying issue with their strategy and processes, demonstrating the growing urgency for enterprises to have a digital infrastructure in place to optimise operational efficiency.

Weighed down by data processes

Data is critical to any organisation as it is the key to understanding more about customers and suppliers. It also helps enterprises visualise what’s happening within the business, while enabling successful decision-making. However, an abundance of new data created every day, that needs to be handled effectively, can significantly weigh down business processes and make it difficult to rapidly react to market changes if data management is slow and inefficient.

While large enterprises have been using ERP systems for years to manage key processes, they are often still using traditional models and analogue systems to process data. In an era where survivability is synonymous with agility, this is not good enough. Data is often spread across multiple systems, exists in a variety of formats, and held in hard-to-access silos. For companies reliant on slow, error prone, manual tasks, data can be nearly impossible to manage. These bad processes drain time and resources and increase the risk of mistakes that lead to poor data quality. Additionally, with multiple departments across the organisation often entering data into spreadsheets and/or exchanging information via email for review and approval, multiple versions of untracked files can increase the likelihood of errors and result in lengthy correction processes.

Automate to survive

Large enterprises with years of historic data and legacy systems don’t need to throw everything out and start again to compete with young and nimble brands. Instead, to improve operational agility

and data quality they can opt for a solution that combines business process automation with effective data management. Using a ‘best-in-class’ flexible automation platform which offers a centralised management solution that can help govern data, increase visibility and eliminate the risk of errors means that data files are not only managed centrally but workflows are also tracked preventing bad data from being entered into the ERP system. This, combined with the automation of key business processes, will ensure that data can be used effectively and efficiently to increase response times.

Relying on name alone is no longer a viable option for big brands to compete in today’s market. Instead, it’s critical that enterprises start handling their data effectively using automated data management tools to speed up processes and secure that critical first-to-market advantage. Failure to do this, will drastically shorten the lifespan of these businesses

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