How To Create Data Validation Rules In Excel

How businesses can achieve data excellence

(Image credit: Shutterstock)

There is no shortage these days in conversations around data, whether involving on-premises or cloud computing systems. At this point, nearly everyone understands its importance related to customer insight, business operations, and digital transformation. It is seen as a valuable source of insight and a key competitive advantage.

Recent research from Experian revealed that 85% of organisations see data as one of the most valuable assets. However, while most companies have an abundance of information, they are in short supply of meaningful insight.

Challenges when it comes to data analytics

Although companies are investing in data and certainly in analytics, most still do not consider themselves to be data driven. When we look at why this is, we see a few key reasons for this disconnect.

First, there is a large degree of distrust in information. The average professional looking at data does not understand how that data got there, when it is useful, and what state it is in. This comes into play especially when data insight contradicts a long-standing norm. While the business wants to be agile and informed by data, this level of distrusted data often influences leaders to fall back on making decisions by gut instinct rather than by informed data insight.

Second, this high degree of inaccuracy is leading to a large issue with data debt. Data debt is a lot like technical debt. You have a set of data assets that isn't necessarily fit for purpose, or it has a high degree of inaccuracy. Unless you take the time to fix that information and govern it properly, you are always going to have a suboptimal data operation.

That means many companies are not fully seeing the ROI or expected benefit from some of the data investments they are making.

Finally, there is a data skills shortage. This doesn't just mean data professionals, like data analysts, data engineers, chief data officers (CDOs), and data scientists. There is also a general lack of understanding around data within the broader business. We see a growing number of companies talking about enabling wider usage of data across the business and wanting to do more with data insight, but very few people across organisations are truly data literate.

This doesn't mean individuals need to write code or complex data workflows, they just need to be able to access, understand, and argue with data. In fact, a majority of companies report that data literacy needs to be a core competency of employees over the next five years.

Luckily, we are seeing many businesses recognize these challenges and start to drive change. While it's easier said than done in many cases, implementing an effective data strategy can help you grow your business by understanding what your data is telling you, and acting on it.

The importance of a Chief Data Officer

Unlike property (controlled by Facilities) or money (controlled by Finance), data is an asset which has unclear or at best confusing ownership. This can obviously lead to delays in gaining insights and a lack of trust in data.

Over the years, data ownership has often varied between a 'centralized with IT model' and a disorganized 'each department for themselves model'. We are starting to see a definite shift to a more organised, yet decentralized model, with a central governance function being put in place. This enables and supports every other function within a business to take more control of the data they need.

This shared risk and responsibility model, when implemented well, helps to manage risk and empower the business at the same time. It also frees up IT management and their departments to focus on the enabling infrastructure, rather than the quality of the data flowing through it.

Putting a Chief Data Officer in place is a visible sign that organisations are investing in data and are more likely to drive a data strategy that will support this business intent.

If not, even under a decentralized model, other decision makers within the business may not be clear on why investing in the fundamentals, such as operational data quality, is the only way to get the most value from advanced analytics and other data-enabled innovations.

Proving the value of data to the entire organisation

While most organisations are already getting value from their data, are they measuring that value in relation to success metrics that matter most to the business?

Data initiatives often fall short because a poor story is told around the success of data and what it means to the business. Very few organisations have the skills to prove the ROI of data initiatives in the context of real business value, like customer satisfaction, revenue or operations excellence.

Stakeholders need to be able to demonstrate value and ROI early on in a data or analytics project with any data initiative clearly tied back to the business strategy, performance indicators, and critical outcomes.

With data literacy now such an imperative, strategies should reflect the requirement to widen access to data and decision-making power to the right people with the policies, skills, and technology in place to support them.

The road to becoming data-driven

Organisations want and need to be data-driven in today's economy. Data has become one of the most valuable assets an organisation possesses, and therefore, the desire is strong to maximize the benefits of this asset.

It is important to remember that change will not happen all at once. As with anything, creating a project that tries to solve every scenario and every situation will often stall and not generate the expected benefits. The good news is that with data it is about finding the quick wins that will make a big difference within the business.

Stakeholders don't have to master all of their data or achieve 100% accuracy to generate value. They need to find the information that matters most and start to make small improvements with small investments. Then, those quick wins will start to generate interest, belief and lead to bigger and better improvements.

Remember, there is no one-size-fits-all approach to achieving your data-informed objectives. Becoming data-informed is a work in progress—it takes time and effort. However, with some new talent and incremental investment, dreams can start to become reality.