It’s simply no longer enough to rely on the ‘too big to fail’ principle. In 1958, large enterprises could expect to stay in the Standard and Poor (S&P) stock market index for more than half a century with little disruption from smaller companies. Over 60 years later, today, this has been significantly reduced to under eighteen years and unsurprisingly, this trend of market instability is predicted to last. According to business consultants Innosight, three quarters of companies currently quoted on the S&P Index will be replaced by 2027.
The rise of new generation digital competitors and ever-changing market dynamics are contributing to this short life expectancy. Many household brands are now under tremendous strain to improve their operational agility to respond to the pressures at play. As a result, integrating technology within the organizational infrastructure has become critical for survival – especially since the Covid-19 pandemic. Yet, many large enterprises are still relying on slow, manual processes to manage their data, hindering their ability to adapt their business models, and become more reactive. This is extremely risky in an era where effective data management and process automation is at the core of digital transformation.
Too big to fail?
Over the past few decades, we’ve seen many high-profile cases of well-established brands relying on their strong reputations and large operations to drive their business strategies. Yet, often, this has resulted in failure, with companies such as Toys R Us and book store chain Borders disappearing from the marketplace. Without a digital backbone to help them react to changing consumer behavior, it is difficult for these large enterprises to match the fast response times of their “born digital” competitors. This was one of the contributing factors to the demise of travel giant, Thomas Cook. After failure to adapt to the new era of travel brought on by online booking platforms and increased digital access, the firm collapsed after 178 years in business. According to the chairman of its digital advisory board, the company didn’t have the capabilities to drive the business forward as it was using ‘decades old’ IT systems and used programming language dating back nearly seventy years.
The impact of the Covid-19 pandemic has also highlighted the growing urgency for enterprises to have a digital infrastructure in place to maintain operations. Management consultancy firm, McKinsey claims that the crisis caused many business leaders to accomplish in ten days what usually took them ten months by accelerating the speed of digital projects and processes. Companies who did not fast track digital transformation found themselves in an incredibly vulnerable position forcing them to slow or cease operations. Fashion retailer Primark, for example saw sales plunge from £650 million per month to zero. With the ‘new normal’ here for the foreseeable, the need to adapt fast to stay relevant is forcing businesses into the ruthless prioritization required to drive a new level of focus.
Age old barriers
While large organizations have been using ERP systems for years to manage key processes, these systems of record and the data they hold need to be plugged into a broader digital infrastructure to increase business efficiency. But with an abundance of data to process and more and more of it created every day, that’s easier said than done. Why? Because many enterprises do not manage their data well. It is often held in multiple systems, comes from multiple sources, and exists in a variety of formats, creating hard-to-access silos that make it nearly impossible to manage information effectively. This is concerning as data is crucial to any digital transformation project. Not only does it hold key details about customers and suppliers, but it also enables enterprises to visualize what is happening within the business, helps determine the cause of problems and aids the decision-making process.
The importance of this data is frequently overlooked due to the weight of traditional business models and analog processes, with many enterprises still reliant on slow, error prone, manual processes to handle their data. From finance to customer services, departments across the organization will spend large amounts of time entering information into labor-intensive, manual spreadsheets, which are then exchanged via email routings for review and approval before it is rekeyed into ERP. This can lead to multiple versions of untracked files, making it difficult to know which version is the most up-to-date or approved, increasing the likelihood of error and poor data quality.
Finally, a lack of emphasis on the interdependence of data and process is leading to ineffective data management which in turn, is making it difficult for enterprises to react quickly enough to changes in the market.
Automation is key to transformation
Younger and more nimble brands that already have digital ingrained in their DNA have been built around a data-driven infrastructure and are capable of managing large volumes of data easily, enabling them to secure that critical first-to-market advantage. While, well-established brands typically have an abundance of historic data which is limited by antiqued systems, hindering their ability to manage data effectively. However, these systems and the data they hold cannot just be thrown out and started again. Instead, opting for a solution that combines business process automation with effective data management will simultaneously improve operational agility and data quality. To do this, a different class of software is required.
A flexible automation platform that can be implemented quickly with minimal programming and engagement from IT is highly advantageous as enterprises can apply their own set of business rules to the data being processed. It should also offer an inbuilt centralized management solution that can help govern data, increasing visibility and eliminating the risk of errors. This 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 agility.
It’s clear that many household brands are struggling in the digital era, and as we’ve seen in the past the decade, failure to adapt significantly decreases the likelihood of longevity. In order to survive, these well-established enterprises need to digitally transform their business strategies by using automated solutions to get their data in shape. It’s do or die!
Andrew Hayden, Automation Expert, Winshuttle