Why should a Data Strategy be a Priority for Organisations in 2021?
Got a business? Then you’ve got data. But the real question is: how are you utilising that data?
We all know what data is and the true value it possesses. But just for clarity, here’s a reminder: Data is the information gathered from research, analysis and observation. This can be presented as measurements, facts or numbers. Without data, businesses, management and individuals alike would not be able to make informed decisions.
It is through the collection of data that corporations, management and stakeholders gain valuable (and quality) information – and with this information can then measure, establish, set goals and make informed decisions. In seeing the true value of data, you will come to learn that data is no longer a by-product but a critical asset.
But how exactly do you unlock the true value of data and use the information to your advantage? A data strategy.
What is a Data Strategy?
A data strategy is your plan of action on how your company will decided how to store, track, use and even share the data collected. Ultimately, a data strategy will provide inspiration and enablement towards business strategies and goals.
Why is a Data Strategy Important?
Let’s start with the statistics.
If we refer to Deloitte’s survey on the advantages of analytics, you’ll find that 49 percent of respondents assert better business making decisions as the most beneficial reason to analysing data, followed by improving the enablement of key strategic initiatives and building better relationships with customers and business partners. With that in mind, you wouldn’t expect that less than 0.5% of all data is analysed and used would you?
It can only be left to the imagination of the possibilities, resolutions and opportunities of achieving goals and establishing effective strategies that many have missed out on. (Source) What this essentially demonstrates is the power data and analytics has on your business if used and analysed correctly. In fact, IDC stated back in 2012 that 22 percent of all data had the potential for analysis. It was also reported that by the year 2020 that figure was estimated to increase 88 percent, to 40 percent. Just imagine what you could do and achieve with all of that data. However, whilst there is an abundance of data that can be both useful and beneficial to corporations, it is imperative to consider one significant factor: poor quality data.
Why? Poor data can cost businesses between 20 – 35 percent of their operating revenue. But it doesn’t stop at a company’s revenue. Poor quality data can also have a detrimental effect on reputation due to customer dissatisfaction, decision-making and the ability to execute strategy. Nonetheless, in an article published by Forbes, Dan Adams, VP of Data Product Management stated that ‘whilst data can often be imperfect and incomplete, with the right tools and processes, data can deliver true, rich insights’.
Enter: Data Strategy.
The use of data strategy allows companies to proactively manage, store and use data in an effective manner – ultimately, avoiding crisis.
An effective data strategy will ensure high-quality data is attained and analysed, which can have a positive effect on business functionality, including (but not limited to) decision making, achieving goals and implementing effective strategies.
What are the Benefits of a Data Strategy?
Specifically, through the use of implementing a data strategy, corporations can benefit from:
- Improved management and records of data
- Unlocking the potential power of your data
- Making better decisions
- Solving problems
- Understanding performance
- Understanding customers – their wants, needs, expectations
- Improved marketing techniques and decisions
- Improved company productivity
Key areas within a Data Strategy
For years, organisations focused primarily on storing data, management of that data and methods of handling that data. Now, whilst certainly an important element of data strategy today, it was singularly focused on storage – not for using the data to plan and improve how you understand, manage, used and acquired data.
In order to address the multitude of decision-making activities businesses and corporations have to make, there are (currently) five core components:
The first step to your data strategy is being able to both identify and understand the data’s meaning. This is where analysis is critical.
No matter the origin, structure or location in which the data has been obtained, you must figure out what it this data is telling you. Naming and valuing data is a core, key factor and method which must be completed in order to use and share data effectively. Such details should be independent. It is also suggested to provide and consolidate business terminology into a glossary – this allows better consistent and clear understanding of data which can contribute towards higher-quality data due to lack of misinterpretation. It is also imperative to provide a means of referencing and accessing metadata i.e., the data’s origin, location, domain values tec.
The second step to an effective data strategy is to store your data in a location that can be easily accessed, shared and processed. Previously, organisations stored all data in one place. Since then, we have gained understanding that storing all data in one singular location is not feasible nor practical. Not everyone needs to access all of a company’s data, typically, they require specific data. Take this image as reference of how to effectively create places to manage and store data. (Source)
The third aspect you need to consider within your data strategy plan is provision. What this means is packaging your data in a way that can be reused and shared easily – but be sure to implement rules on how your data can be used along with access rules and/or any other regulations you deem necessary.
Businesses today are pretty much dependent on data being shared and distributed. Why? Because obtaining specific pieces of data support corporations operational and analytical needs. And, if a company well and truly see data as an asset, it must therefore be packaged and readily available to be shared. To therefore treat data as an asset, provisioning must be implemented into your data strategy.
The fourth aspect to consider: Processing.
The process stage of a data strategy refers to moving and combining data that currently reside in different systems. This process will unify the data in which has been obtained from varying sources. As whilst raw data is uniquely valuable, it has not yet been reviewed, analysed or even corrected to figure out what this data is telling you nor would it even be “ready to use”. The processing of data is the (somewhat most important) phase of the digital strategy. Here is where the magic happens. It is where activities are carried out to “evolve” the data, transforming it from its originally raw form into a valuable good.
The fifth stage of developing a data strategy is governance. Data governance refers to the collection of policies, roles, processes and metrics – ensuring effective and efficient use of information, contributing towards the corporations’ goals. In simple terms it’s how businesses protect, manage and utilize their data.
Establishing a data strategy should be a priority for organizations as, as data increases year after year more value can be taken from it. But it also becomes harder to handle, analyse and govern. Creating a data strategy allows you to better analyse and manage data, contributing towards successfully achieving company goals and implementing effective strategies.
Does Shaping Cloud offer Data Strategy services?
The answer is, YES. At Shaping Cloud, we offer first-class Data Strategy, Migration and Governance services that can give you invaluable insight into your Data. Why not get in touch with a member of our team to book your health check today? Contact us