How can IT leaders effectively overcome the challenges of data complexity to drive significant business value?

How can IT leaders effectively overcome the challenges of data complexity to drive significant business value?

A new report from Appsbroker & CTS revealed businesses use less than two-thirds of their ‘data brain’, showing that lack of timely and accurate data is leading to missed reporting deadlines, customer complaints and bad decisions. We get insights from Chris Gorton, EMEA Managing Director and Senior Vice President, Syniti; Jason Beckett, Head of Technical Sales EMEA and CTO, Hitachi Vantara; and Rajesh Ganesan, President, ManageEngine.

Appsbroker & CTS, a leading Google Cloud-only consultants, recently released a new report showing that IT leaders are still struggling to get full value from their ‘data brain’ – the data an organisation captures and analyses to drive business value. 

The data maturity report, Making the Most of Your Data Brain, revealed most (91%) of the 150 UK IT leaders surveyed said they have a specific mandate from their board or executive team to make their organisation more data-driven and data-centric. However, almost three quarters (73%) still struggle to transform data into delivering significant business value. Key findings include:

  • Not firing on all cylinders: Businesses are using less than two-fifths (39%) of their data brain – with 69% admitting to hoarding data in data lakes and using just a fraction of it.
  • Data friction persists: 88% of organisations said they face hurdles to becoming data-driven, with the top-ranking issues being IT and data complexity, legacy systems and a lack of skills and resources.
  • Data citizens left out in the cold: 87% of respondents think empowering citizen developers will help businesses overcome the data skills gap, but 81% lack the skills and know-how to enable data citizens.

This lack of access to timely and accurate data has serious ramifications for businesses, as 39% confirm they have overspent or underspent on projects. And as far as they are aware, 37% of respondents have made decisions based on inaccurate data, and 36% have made inaccurate forecasts – although the true amount could be even higher.  

Furthermore, 31% have suffered customer complaints, 31% have delayed product or service launches, 27% have missed reporting deadlines (including businesses from heavily regulated sectors such as financial services) and 25% have missed revenue opportunities.

“Leaders are using data for big business-defining decisions, so they’d better be confident that information is right,” said Matt Penton, Head of Data and Analytics at Appsbroker & CTS. “Reporting bad numbers can have very serious and public repercussions, and customer complaints can quickly lead to churn. Unless you’re selling grated unicorn horns, customers can and will go elsewhere. These are the tangible costs that can sink a company when data is used ineffectively.”

IT leaders reported using over 30 different data sources on average. As the volume and complexity of data architecture increases, many businesses are struggling to keep pace:

  • Less than half (46%) of IT projects that rely on data run on time, within budget and to the intended scope – a source of frustration, stress and cost for internal teams.
  • Despite the move to more open technology stacks and APIs, 81% of IT leaders say integration issues still plague the IT industry – with 79% lamenting that ‘it’s near impossible to get a single organisational view’.
  • Three-quarters (76%) say the complexity of their data architecture is increasing exponentially. As a result, 85% say associated costs are increasing every year, and 69% say it is becoming increasingly difficult to manage.  

While complexity will inevitably continue to grow, Penton argues this doesn’t have to result in ballooning costs and confusion – simplification is the key: “Don’t try to boil the ocean – start with a smaller data set and then expand to ensure you are getting things right, and doing it in a timely manner. Complexity isn’t going away, but automation, common tooling, low-code and no-code can make it easier to manage data.

“By taking a structured and realistic approach, speaking with experts and deploying the right tools, every business can unlock the power of their data brain.”

Chris Gorton, EMEA Managing Director and Senior Vice President, Syniti

Chris Gorton, EMEA Managing Director and Senior Vice President, Syniti

We all know that data has the potential to be very valuable. But the reality is that IT leaders, and the organisations they work for, are facing serious challenges when it comes to managing and governing their data. As a result, they struggle to leverage their data’s true value and risk falling behind their competition. 

This is widespread. A recent survey by the UK and Ireland SAP user group found that just 7% of the IT leaders questioned were very confident when it came to their organisation’s data quality and accessibility. Of course that has implications: 82% of the same respondents said data management challenges will slow their organisation’s adoption of AI technologies for example, and 89% reported that data silos stifled real-time decision-making.

But although data complexity is common, it doesn’t have to be inevitable. There are steps IT leaders – and their C-suite – can take to get to grips with their data.

Adopting a ‘Data First’ approach, that is prioritising data quality at the start of a transformation journey, and developing strategies and governance, is crucial. It means getting to know which data is business-critical and which must be as accurate as possible. It’s also understanding how that data links to business objectives, how it supports decision-making and where poor data accuracy has the most impact. Then, drilling down into how accurate that priority data is now and how it is affecting business performance.

Next, setting meaningful goals will help to untangle data complexities. I say meaningful, because although some data does need to be 100% accurate, it may not be possible to guarantee that every single piece of data is correct at all times. So, it’s important to know the level of inaccuracy that can be tolerated.

Then, bring in the C-suite. The research found that data strategy still tends to sit with the IT team (62%) with low C-suite ownership (3%). This doesn’t make sense. Data and its governance ultimately impacts the bottom line, so the leadership team has to be involved. It’s not just about having senior buy-in, it also signals to the rest of the organisation that data and data governance are important.

Prioritising data is really the only way to overcome complexity challenges and properly start to benefit from its value.

Jason Beckett, Head of Technical Sales EMEA and CTO, Hitachi Vantara

Jason Beckett, Head of Technical Sales EMEA and CTO, Hitachi Vantara

In today’s hyper-digital age, IT is no longer just a support function but a central part of business strategy. It drives decision-making processes and provides valuable insights for business growth. However, the potential of data is often hindered by broader challenges such as rising data complexities.

It is estimated that the data we generate, collect and consume is projected to surge from approximately 50 zettabytes in 2020 to more than 180 zettabytes by 2025 – an astonishing figure. At the same time, a large proportion of this enterprise data is unstructured, making it far harder to secure due to its volume, variety and inherent lack of organisation. 

As data volumes continue to grow exponentially, the complexity of managing multiple environments can lead to a lack of integration across data sources that limits a company’s ability to extract business value. A survey conducted by Hitachi Vantara revealed over 40% of businesses experience revenue losses from downtime, cloud complexity and legacy constraints. To effectively overcome these challenges and drive business value, IT leaders must adopt the right cloud strategy and modernise their IT infrastructure. 

First, when exploring cloud adoption, businesses must choose the most suitable infrastructure to meet their operational needs. Public cloud services, with their scalability and flexibility, are ideal for organisations seeking quick access to resources, especially for smaller projects with variable workloads. On the other hand, a private cloud offers dedicated resources and heightened security, making it suitable for industries with stringent compliance requirements. Although both have their merits and drawbacks, the ultimate win case scenario is the adoption of hybrid cloud, which gives organisations the combined strengths of speed, flexibility, scalability and more robust data security.

Second, as data continues to explode, business leaders are under pressure to transform their IT infrastructure to thrive better in a cloud environment. Organisations can accelerate their technology modernisation through cloud-based practices, which include transitioning to a cloud operating model for managing traditional, cloud-native and mission-critical applications and workloads.

With research now showing a shift from traditional IT infrastructure purchase/lease models to IT-as-a-Service (ITaaS) with subscription- and consumption-based models, this shift is driven by the need for faster, more reliable and sustainable technology delivery to a wider range of locations. ITaaS solutions can enable this by simplifying IT infrastructure management, facilitating a smoother journey towards enterprise modernisation.

By adopting the right cloud strategy and modernising IT infrastructures, IT leaders can not only navigate the complexities of hybrid cloud environments but also unlock significant business value. These steps will become increasingly important as we continue to face the age of the data deluge, enabling businesses to harness the power of data effectively to drive innovation and growth.

Rajesh Ganesan, President, ManageEngine

Rajesh Ganesan, President, ManageEngine

Organisations are producing more data than ever before, and it’s this data that is increasingly relied upon for making business-defining decisions. That means it’s imperative organisations are working with accurate information; otherwise, data can quickly become a liability and not an asset. Digitalisation is allowing businesses to deliver innovative outcomes, helping them build differentiation. Examples of such outcomes include multi-channel, AI-powered customer experience, enabling secure and hybrid workplaces and so on.

As the complexity of data inevitably continues to grow, proper processes are essential, namely because most traditional workflows struggle to handle the increasingly huge data volumes efficiently. Inherently, this means the business needs to have a strong foundation for managing data, which is the basis for driving these outcomes. Businesses normally have data originating from multiple sources, creating a challenge in identifying bottlenecks or issues that might cause delays and reduce visibility.

It’s not uncommon for an organisation to have data, processes and tools all in silos and not know how to put them together. Likewise, teams often use numerous tools, meaning there’s no consistency and limited collaboration throughout the organisation – this invariably makes it harder to use data as an asset and limits its potential to generate actionable insights.

The first step is to cultivate a data-positive culture. This means choosing the correct software, investing in security and leading from the top. Clear policies and procedures should also be put in place to avoid siloed data and ensure greater data visibility. IT leaders should take this as a top technology and business priority and strategise the management of complex data, including identifying the challenges. Data security and privacy (data protection) is crucial, and processes and tools should be put in place to achieve it.

Businesses should also focus on building an ecosystem that is connected, adaptable and capable of responding to and managing disruption in real time. A crucial part of this is implementing a successful DataOps strategy. This helps organisations achieve enhanced business agility, increase productivity and improve decision-making. The introduction of new technology capabilities such as AI can also make analysing large data sets easier than ever. For example, GenAI tools help with data visualisation and can mitigate the impact of missing or incomplete data.

As data volumes continue to increase, businesses need to focus on approaches that both manage and allow analysis of data, providing insight that benefits the organisation. DataOps tools and new technology will play a crucial part in this, as will a more holistic approach to data throughout the organisation with defined data strategies. Data management will continue to be of utmost importance and will be a top business priority.

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