How Data Strategy Can Help Your Organization

What Is Data Strategy Anyway?

Data strategy is a way to utilize data to produce insights useful for the business. Without it, the data itself can become a liability as it's both expensive and useless. Gone are the days when data was simple, small, and easy to process, making any strategy virtually unnecessary. These days we live in a world of ever-growing data, significant business challenges, and fierce competition (globalization). With the plethora of data available, both internally and externally, it's easy to get lost inside it and not leverage it appropriately. Data strategy promises to help with all this, adding value in hands-on ways without breaking the bank.

Key Aspects of Data Strategy and Its Use Cases

Data strategy encompasses several activities, such as sourcing & collecting data, data governance (including privacy and cybersecurity matters), data analytics, tech & data infrastructure, and building data competencies in an organization. Each of these is a whole field by itself, making data strategy an interdisciplinary field. Most importantly, data strategy is directly aligned with business strategy, so it's not a purely technical field.

The fundamental areas of data strategy include the following:

• using data to make better, fact-based decisions
• helping us better understand customers & markets
• using data to offer smarter services & more intelligent products/services
• improving & automating business processes with data
• monetizing data

Often a data strategy may involve more than one of these use cases, while it's likely that most of the aforementioned activities will come into play too. That's why it's not an easy field, but certainly an essential one.

Data Is Without Inherent Value But…

Data may seem like an asset, and in many cases it is, but its value is essentially zero. This statement may come as a shock to many people, but it's true. Data on its own doesn't do much (other than look nice, perhaps). Where is the value in that? Fortunately, with many data analytics options available to us now, we can turn this data into useful information (aka insights) that can help us make better business decisions, understand where we stand, figure out how to meet our strategic objectives, etc. If data is the new oil, then analytics is a powerful engine that uses that oil. Of course, not all analytics engines are created equal, and even though some of them are impressive, they may not be the best fit for your organization. A racecar engine may be great, but do you really need it if all you want is to get from your home to the supermarket and back? With the plethora of options in analytics today and the overly technical perspective of most analytics professionals (who seem biased toward those race car engines!), it's hard to decide on which option to go for to make the most of your data. Fortunately, data strategy addresses this matter too.

Data and Big Data

We’ve all heard of big data, but how does it differ from conventional data (aka small data)? Well, big data has the following characteristics, aka the 4 Vs:

1. Volume – big data is enormous and impossible to tackle with a single computer. Oftentimes, the cloud comes to the rescue.
2. Velocity – big data involves data streams, which are collections of data continuously updated, like social media feeds, financial data, sensor data, etc.
3. Variety – big data comes in different forms, from structured data in various conventional databases to unstructured data found in videos, to semi-structured data like the data in images, modern databases, and the web.
4. Veracity – big data isn't always reliable since certain parts may be intentionally or unintentionally fake (e.g., the various bots roaming social media these days).

Value is sometimes considered the 5th V of big data, though for it to come about, analytics is needed, as we saw earlier. However, when big data is analyzed properly there is a lot of value that can come out of it. Partly, this value is because even the weakest signals dwelling in it can be harnessed and used to make useful predictions.

When You Don’t Have Enough Data

What about when the data at your disposal isn’t enough? Big data is great but does it apply to the average organization that's not as advanced in data technology? These are questions that many business people have often asked and led them to believe that data isn't their thing. But this doesn't have to be the case. Nowadays, there are options for accessing big data as an external source, complementing the internal data you have. Naturally, this data you have in-house is often better value for money, and you have more control over it. But the external data opens up more possibilities, is more varied, and it's less likely to be biased. So, given the initiative, any organization can obtain access to "enough data" to achieve its strategic objectives. Naturally, data strategy is essential for gauging your options and making an informed decision on this matter.

Data Tech Waits for No One

Data tech may be great, but it's also a challenge to keep up with, especially nowadays. Specifically, there are plenty of innovations these days that dramatically change the tech landscape, along with the involved data. Things like cloud computing (it's more than just a storage option!), edge computing (doing analytics at or close to where the data is collected), blockchain (not just for cryptocurrencies), advanced machine learning, internet of things (e.g., smart devices), affective computing, virtual & augmented reality, cognitive computing, and robotics. All these also affect the business world, as they create new opportunities, develop new options for collecting & processing data, etc. A comprehensive data strategy takes these into account, along with the changing business environment that accompanies them.

Next Steps

So, what now? What can you do to put all this into practice? For starters, you can learn more about data strategy and its impact on an organization today with clear value-adds and optimizations. Then, you can explore your options for developing and applying a data strategy in your organization. If you are serious about it, you can even get a consultant to help you or, perhaps, hire someone for this role. Regardless of the size or industry of your organization, one thing is for sure: data strategy can help make things better, making your organization more data-driven and fact-based.

When I’m not writing articles for beBee or taking data-related courses, I offer consultation to various organizations via GLG. I also author technical books, develop video courses, and mentor data professionals and beginners in data analytics. Lately, I've branched out to data strategy, a fascinating area integrating many of the data fields I’ve delved in over the years. Feel free to reach out to me for more information regarding how you can leverage my services for your organization!