Data has become one of the most valuable assets any business has — not just for digital giants like Google, Amazon, or Facebook, but for small and midsize firms, too. Companies may use data to make better decisions, gain a better understanding of market trends and customers, create smarter products and services, improve corporate operations, and generate new revenue streams.
But what does this mean for those tasked with evaluating the return on investment of a data strategy and business use cases? How do you know what constitutes a valuable data strategy when you're not a big data expert?
Why every company needs a data strategy
If every company is now a data company, it stands to reason that every company requires a data strategy. If you don't have a data strategy, you risk missing out on the immense potential business value data offers, whether you're a small, family-run business or a large multinational.
The data strategy allows you to define how you intend to use data, define your top data priorities, and devise a strategy for achieving your objectives. It's the most reliable way to get to the heart of your company's data demands and devise a strategy for the future.
With technology advancing at such an incredible rate these days, many businesses, particularly those on the smaller end of the spectrum, are finding it difficult to keep up. This may result in inaction or a strong desire to overlook the big data revolution. Or it may cause the organization to rush into new data opportunities without giving them adequate attention, resulting in a large amount of data that isn't particularly beneficial to the business. Neither method is ideal for extracting the greatest value from data.
That, in a nutshell, is why every company needs a data strategy.
Key elements every data strategy should cover
Start with your key strategic data use cases/data priorities
In essence, this entails determining why and how you want to use data. However, keep in mind the phrase "strategic," as this is an important component of determining how to best use data. Data use cases and data priorities must always be related to your company's overall business strategy — in other words, how will you use data to achieve the company's primary strategic objectives and solve its most pressing problems? Bernard Marr has a handy template for identifying data use cases on his website.
Companies can use data in a variety of ways, but they mostly begin by using it to help them make better decisions, which can lead to data priorities such as:
Understanding and enhancing staff engagement
Providing a more personalized consumer experience
Whatever use cases the company has established, the finance professional's job is to assess the financial effect and return on investment of possible data initiatives in relation to the company's strategic objectives.
It's also critical that the data strategy concentrates on a manageable set of use cases. When working with company executives to establish their data strategy, it's helpful to identify one to five use cases, as well as one or two quick wins (small data projects that can be implemented relatively quickly to demonstrate successes). If you go above that, your data strategy will become cluttered and unrealistic.
Then set out the requirements and challenges for each use case
After you've figured out how to use data, you can move on to the data strategy, which should take into account the needs outlined below. Once again, Bernard Marr has an easy-to-use data strategy template with all of these components. You may notice that the template highlights cross-cutting concerns/challenges that apply to all use cases. This is done because, while each use case/data priority is unique, they will almost certainly share some of the same issues or challenges.
So, moving through the template in order, the fundamental aspects of a good data strategy are:
Data requirements: What data does the company require, and how will it obtain that data?
Data governance: How will the company deal with concerns such as data quality, ethics, privacy, ownership, access, and security?
Technology: What are the software and hardware requirements? This will include technologies for gathering, storing, analyzing, and sharing data insights. Is the technology in place to support the data strategy already in place at the company? If not, the company must determine what is required to meet such criteria.
Capacity and skills: For many companies, a lack of data knowledge and abilities is a major concern. So, how will your company bridge the data skills gap? This could include things like staff training, employing new talent, partnering with outside vendors, and so on.
Implementation and change management: What obstacles must be addressed in order to properly implement the data strategy?
A strong data strategy should address all of these areas while also identifying common themes and difficulties across your data priorities.
Important data strategy errors to avoid
When reviewing a data strategy, it is useful to be aware of the most frequent errors that companies make. These are some:
Starting with an outdated business strategy: The data strategy must be aligned with a current and relevant business plan in today's digital world.
Not linking data uses/priorities to strategic business goals and challenges: Too many businesses build their data strategy on interesting or easy-to-implement use cases, rather than use cases that lead them to their goal.
Only considering internal, traditional data: Data nowadays arrives in a variety of formats and from a variety of sources. An effective data strategy should consider all data sources, including photo and video data, as well as external sources like social media platforms and large data brokers.
Minimizing or overlooking the ethical, privacy, and legal issues: Because consumer trust is so important, good governance must be properly considered.
For today's companies, having a solid data strategy is critical. These pointers will help you confidently assess your data strategy and understand how to use data to fulfill the strategic objectives of the company.