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Is your business about to fly blindly into an economic storm, powered by unreliable data?

Is your business about to fly blindly into an economic storm, powered by unreliable data? 1

By Ronnie Wilson, Group Executive Vice President, Serviceware SE

2020 has been quite the year. As if there wasn’t enough going on as the year began – the news then was dominated by Brexit and the perceived threat of the death of the High Street – in March, the UK and many other countries went into lockdown. Without doubt, this has brought about one of the biggest upheavals to business and purchasing behaviours in living memory. And, as the world continues to navigate through the ongoing ramifications of the pandemic, businesses will be required to continually pivot and re-strategise.

Turbulence ahead

Since that shift, as well as navigating traditional issues such as Brexit and the impact of e-commerce, CEOs must be ‘innovative anticipators’, and lead the crisis response whilst setting their companies up for bigger wins once the post-pandemic dust settles. Much has been discussed around cost-saving methods – from identifying billing errors to negotiating quick wins – but gaining cost transparency and cost control, as well as digitising and automating service processes, are now crucial. Ultimately, companies need to simultaneously cut costs whilst accelerating their digital transformation to keep up in a challenging marketplace.

Although this may seem like a mammoth task, the c-suite can be encouraged by the fact that 2020 can also offer them technologies that enable them to adapt. Specifically, business data analytics tools are key drivers of growth and success. That said, digital transformation, which businesses are under so much pressure to achieve, often adds layers of complexity to data analysis. From additional vendors and applications, to methods of accessing services (e.g. legacy and on-premise vs. cloud), this all creates huge quantities of cost and usage data to analyse.

The challenge the c-suite faces now is how to gain one transparent view across all business expenditure vs the value generated. Those who do will be best placed to be able to spot money saving opportunities and reinvest in future projects in order to enable growth. But how can the c-suite achieve this when they are often relying on inaccurate, unconnected data to make these decisions?

Navigating through a hail storm of inaccurate data

Many organisations who are investing in innovation are taking ‘leaps of faith’, rather than basing decisions on systematic analysis, which prevents them from evaluating true success. Whilst businesses data-crunching is not a new concept, the data is often outdated on arrival. This can eventually lead to errors further down the line – and potentially puts billions of pounds of risk into companies’ operations .

When it comes to decision making, data that it is captured in real-time and analysed effectively is a necessity. After all, any inaccuracies that mean you are unable to turn data into reliable information  renders that data utterly worthless. Ultimately, the value in data lies not in the data itself, but the information and fact-based decisions that can emerge from it.

Unfortunately, while many have tried to leverage data, not everybody has been as holistic or far-sighted as the market leaders – and that could prove costly in an increasingly complex landscape, where the ability to respond to changing demand is crucial. Half-hearted, outdated or inefficient data handling will leave businesses ‘flying blind’ when it comes to decision making. Not only will these businesses not be able to truly understand the consequences of their decisions but, ultimately, they could be stunting future growth. This can be extremely dangerous for businesses at the best of times, let alone during the current economic climate – where every decision can be ‘make or break’ in today’s turbulent landscape.

What is holding businesses back?

In short, businesses are being hampered by ‘duff data’ – which means low-grade or incomplete/outdated datasets, poor data visibility across the organisation and/or inefficient handling. There are also instances where different data sets, addressing the same issue, present varying conclusions – preventing organisations from obtaining that ‘one truth’. Errors due to manual data entry can also contribute to inaccuracies – leading to devastating consequences should they not be realised before being used as a basis for decision making.

Such data is acting as a  barrier, stopping organisations from moving forward and driving growth through new technologies such as artificial intelligence (AI) – which has been considered the most disruptive technology by 62% of CIOs, and the technology with the greatest impact by 42%.

Some businesses congratulate themselves on collecting data, while failing to recognise that their processes are not joined up (leading to data silos and failure to integrate business intelligence), are inflexible or otherwise fail to provide the facts needed for effective decision making. It is probably true that some, local data is better than no data, but it is certainly true that poor data management costs businesses money. It also leaves them in the starting blocks when it comes to an agile response to change, with accompanying needs to manage costs and streamline operations. Sub-standard data handling has many causes, but the most common ones include:

  • Spreadsheets that are out of date or include multiple manually entered errors
  • Data silos from multiple legacy applications that do not integrate or meet business needs
  • Inflexible ‘organisation-wide’ solutions that are not modular, or are limited in scope, so cannot be integrated with new applications as needs arise. Nor can they be scaled according to financial needs
  • Complex operational processes, including IT data processes
  • Poor collaboration across the business

Organisations that rely on duff data are essentially flying blind, and that is very bad news indeed when times are turbulent. In addition to inaccuracy, duff data can lead to late reporting, cost allocation confusion and a lack of effective scenario planning. Recent events have put huge pressure on CEOs and CFOs to make key decisions around costs, operational processes and strategy, often at short notice and in a rapidly-changing landscape. In that context, duff data can be lethal.

Many of the most famous names in business are now fighting for survival. How many of those can honestly be described as understanding and promptly responding to their business/customer demands? And how many more will follow?

Tough times demand total transparency

There is, for once, a simple answer to the challenges facing business now. The c-suite has no choice but to get on top of every single operation and process point, every cost and opportunity, using real-time information that is definitely reliable. Taking a holistic view and targeting all costs, to free up money for investment into digital transformation, will help secure liquidity in a downturn and ensure that businesses don’t lag behind. However, using partial or siloed information could seriously harm the organisation, now more than ever.

This calls for an integrated, high-performance and, above all, flexible solution that generates reliable information from all parts of the business on which decisions (about cost, process, operations, business direction and everything else) can be based. If that means an initial investment to analyse the value of legacy systems vs cloud-based solutions, then it’s a cost easily justified. It’s not quite as easy as just picking and using one of the many software tools in the market, but financial management tools are vital in the collection of vital real-time operational, project and vendor cost data. These tools enable fact-based scenario planning and in turn help ensure that innovation and digital strategies take centre-stage in optimising services and refining processes – whilst adding value. In a nutshell: they eliminate the risks of ‘duff data’, whilst enabling smart financial decisions.

In a rapidly-changing landscape, the like of which has not been seen for decades, businesses that still rely on outdated, incomplete, or inaccurate data will struggle. Meanwhile, it is those that make decisions based on high quality, transparent data who will thrive.

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