Four key data and analytics trends for 2021 from TrueCue
Digital transformation has been a key objective for many businesses for some time. In fact, prior to the crisis, as many as 70 per cent of organisations reported having a digital transformation strategy, or that they were working towards one.
Many of these strategies were historically driven by desire for innovation, to optimise processes and to outperform competitors. Covid-19, however, supercharged those ambitions to absolute necessity and a need to survive.
Much has been reported about the pace of change, including rapid migration to the cloud and the move to support remote working for organisations of all sizes. But increasingly – with hopes rising as vaccine rollouts continue across the world – companies are starting to move their mindsets from short to long term, not content with just surviving in the new world but thriving.
Many will need to make up lost ground and become more efficient in their operations, whether this be through cost optimization, adapting supply chains or accelerating digitalisation. Whichever way, organisations will need to increasingly rely on their data, to ensure they are making the right decisions at the right time
With this in mind, TrueCue’s experts have identified four key data and analytics trends that will characterise the most forward-thinking businesses in 2021 and beyond.
Understanding the ROI of data and analytics initiatives
The focal point of quantifying ROI is so businesses can prioritise investment. Ironically, it can be quite hard to quantify the investment from data and analytics initiatives. Some benefits are easy to measure, such as avoiding time wasted on repetitive tasks. Others, however, are much harder, such as quantifying the benefit of making “better” decisions.
Many organisations will have a means of measuring direct ROI but often neglect the value which can be gained from understanding the approach needed to achieve that ROI in the first place. For example, a business may measure how much time is saved on repetitive tasks being automated but fail to understand the impact of making quicker and/or better decisions. The other consideration when understanding ROI is the need to establish a baseline and capture data to track cause and effect. Often, projects are embarked on to achieve a set goal – for example, reducing admissions into hospital. Once the project is finished, you may see a reduction in hospital admissions, but without capturing the data properly you can’t attribute it directly to the project output.
Our opinion is that before embarking on any data and analytics initiative, the range of likely benefits and business impacts should be discussed, understood and, to the extent possible, measured and quantified. This will also help the business to prioritise different data and analytics initiatives. Our experience tells us investment is often mistakenly focused on the “visible” elements (such as front-end dashboards), rather than the “behind the scenes” elements (such as robust data management), which are hugely valuable but not seen by most end-users.
In 2021 and beyond, successful business leaders should have their desired outcomes front and centre of any initiatives, and then build data and analytics initiatives around these to ensure a stronger ROI, which will help sustain business success.
Historically, far too many businesses have been slow to properly measure the ROI from their data and analytics investments. Often, they rely too heavily on technology-driven evaluations that overlook the outcome-driven priorities. We believe it is important to make sensible investments in platforms that can save valuable time. ROI must also focus on efficiencies in operations and identification of new lines of business once the technology platforms are in place.
The role of the CDO will be more prominent
The role of the Chief Data Officer (CDO) will undoubtedly become more prominent in 2021, with budgets specifically devoted to data and analytics also increasing.
Over the last five years the position of the CDO has grown in prominence, and they’re now responsible for overseeing a range of data-related functions that may include data management, data governance, creating a data strategy and establishing a data and analytics culture throughout the organisation. According to Gartner, very early adopters of the role focused almost exclusively on data management. Over time, the position has evolved to embrace analytics and to help facilitate digital transformation efforts.
Today, the role has become much more overarching and aligned with strategic business objectives, responsible for a host of initiatives including revenue growth, cost optimisation and mitigating risk. We are also seeing greater requirements for this role in smaller organisations too. In fact, for SMBs, even if they don’t have a standalone CDO role by name, someone should be taking responsibility for the organisation’s data.
Because of this, we expect to see a rise in the “decision data” role. This is where a team or individual, takes responsibility for leveraging the insights extracted through data, before analysing and transforming this insight into actionable information which can be used to aid business decision making. Importantly, this role should be separate to IT, Head of IT, or the CIO, as they have very different responsibilities.
The best CDOs perform a hybrid role. Someone with an understanding of how organisations work and the commercial elements of a business paired with knowledge of the limited life-cycle of data and analytical projects.
However, in order to achieve this, they must “sell” the overall vision and strategy for data and analytics and the measurable business benefits, while also overcoming any stakeholder objections and underlying change resistance challenge.
Smarter approach to sharing and governing data
Data governance is often closely associated with data security, and while it is absolutely imperative that data is handled in a safe and secure manner, an overcautious approach can result in data being locked up and only made available to a minority of users, which reduces its utility to the organisation. In fact, good data governance should be about liberating information, such that it can be shared in a secure and appropriate manner with those that have use for it. In October 2020, a Gartner survey of 2,000 CIOs, concluded that by 2023, organisations that promote data sharing will outperform their peers on most business value metrics.
Thus, establishing a centralised, curated and governed source of non-sensitive data and a trust-based, risk-aware data-sharing model across the business will become increasingly vital in unlocking the benefits of data analytics. Not only should this account for security and lineage governance but, equally, culture and skills as well.
Those organisations that leverage data and analytics most effectively will be those with a clear focus on aligning their technical and business strategy skills, structuring the entire organisation to be more data-centric and creating a collaborative culture of data sharing across the organisation. Having a strong CDO or dedicated data team is key to this, rather than it being dispersed and scattered across the business.
Data analytics – pilot to production
More organisations will continue to pursue data-centric initiatives in 2021 – however, what will really separate the leaders from the pack will be those that can productionise their solutions such that the business can capture the full range of benefits, on an ongoing basis. This means that data solutions are moved into Business-As-Usual (BAU) processes (rather than being ad hoc or localised) and, crucially, that the solution informs and drives decision making. Analytical solutions by themselves add little value unless they drive decision making and action – it is this “last mile” that drives benefit into the business.
In our experience, most businesses are good at the pilot stage, for example where good ideas are translated into experimental analytical solutions by a capable data team. However, many struggle to move beyond this, whereby the solution is moved from “project” into “production”, and is made available on a permanent basis to decision makers. In order to be successful at this, the business must be closely involved, with a focus on what decisions need to be made, and what action will be taken as a result.
Ultimately, the benefits of improving your data and analytics maturity levels are widely recognised – improved forecasting, generating better actionable insights and heightening your understanding of competitors, to name a few. Understanding your level of data maturity is therefore essential if you want to realistically achieve your organisational goals and be able to make better informed business decisions. Early adopters are likely to be nimble to any instability faced over the coming months. Those which don’t will lack the foresight to address potential challenges.
Despite society living with Covid-19 for more than a year, we are still yet to see the full impact of the pandemic on the economy and organisations. But amid the crisis many businesses have demonstrated great resilience, digging deep to ensure the survival – and, if anything, the pandemic has shown that rapid change can reap huge rewards. In order to progress in these uncertain times, it is critical business leaders continue to leverage the investments made into digital initiatives, through data and analytics, in order to facilitate smarter business-decision making.
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