“Data-driven” is a commonly-used term these days. Everyone is saying it, but do they really know what it means or how to develop data-driven operations in their businesses? There are many steps to becoming data-driven, whereby decisions are made based on data, not intuition; the early building blocks of data discovery and strategy are essential to becoming a truly data-driven enterprise.
SEE: Data governance checklist for your organization (TechRepublic Premium)
Once you’ve developed an initial understanding of your data and what you can do as a data-driven business, your organization’s workflows, processes and goals can be optimized for better results and greater business value. In this guide, learn what it means to be data-driven, and check out some tips for creating and sustaining an effective data-driven business strategy.
- Beginning your journey toward data-driven operations
- Using your data: Sales vs. operational efficiency
- Aligning your business and data strategies
- 5 ways to ensure success in your new data strategy
- Becoming truly data-driven
Beginning your journey toward data-driven operations
Just because you have data analytics tools and use data to make decisions doesn’t necessarily mean you are a data-driven organization. Truly data-driven companies handle their data just as you should handle employees: by creating a safe and secure environment where they can thrive.
SEE: The data-driven decisions bundle (TechRepublic Academy)
The first step toward becoming data-driven and creating an ideal data environment is understanding exactly what data you have, where it lives, how it is used and how accurate it is. Once you have identified these critical factors, you can begin your data journey and set your specific goals, whether it’s improving the customer experience or introducing new services.
Any business-to-business or business-to-consumer company can make better use of its data. However, the value will vary from sector to sector. Retail, for example, can extract lots of behavioral data about purchases and make relevant recommendations. For a law firm or advertising agency, it might take a little more effort to identify and optimize valuable data assets.
Using your data: Sales vs. operational efficiency
At a basic level, data-driven businesses fall into two categories: those that use data to boost sales and improve customer service and those that use data to enhance operations and processes.
Determining how your organization should use data to impact business objectives is an important first step toward aligning your data strategy with real business value. Depending on your line of business and the market you’re targeting, either a sales, an operational or a combined focus might be most effective.
Using data for better sales and customer experience
To achieve sales efficiency, a game developer might measure how long people are playing the game, the length of time between games or popular character choices. By utilizing these datasets to understand user habits and behaviors, developers can shape the design of the game, from in-game rewards to color schemes.
From this new knowledge, the developer can move forward to capitalize on and monetize these insights. In B2C scenarios like this one, consumers are frequently asked to provide feedback on their experiences, which creates additional data points that can drive development decisions.
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Using data for operational efficiency and process optimization
On the other hand, we have engineering companies that primarily use data-driven strategies to enhance their current operations, processes and procedures. From monitoring robot performance to evaluating plant efficiency, these companies often use data generated by the Internet of Things to give them an increasingly granular view of data.
Aligning your business and data strategies
For the many companies trapped in a traditional frame of operations, they need to adapt to the changing expectations of the modern market and put data front and center. Too often, data strategies are not driven by executive sponsorship and consequently are not supported with the processes, teams and technologies they need to succeed. An effective data strategy requires executive buy-in that trickles down to all employees.
SEE: Best business intelligence tools (TechRepublic)
For the best outcomes, a company’s data strategy should be developed to align with its business strategy. This alignment will ensure data is seen not only as a priority but as an important step toward achieving business goals, which will ensure data teams receive the resources, funding and attention they need to make data-driven decisions for the business.
5 ways to ensure success in your new data strategy
Once you have the internal resources secured and have decided how best to use your data, it is time to put your new data-driven strategies into practice. These are five lessons you must pay attention to while getting started.
Don’t skip the data discovery phase
if you don’t understand your data, you cannot make useful decisions with it. Before going any further into a data strategy, businesses need to go through the data discovery process, which involves learning about the locations, purposes and metadata surrounding your data. A variety of top data governance software solutions support companies through the data discovery process.
Define the end result you want to achieve
Start your data-driven journey with an idea of where you want to end up. I have worked with companies who have come to us looking for data project guidance but with no idea why; it was simply a box-ticking exercise. That approach is destined for failure, while organizations that have a clear vision of the endpoint are more likely to succeed.
Recognize that tools don’t solve all your problems
In many other areas, say networking or security, it is not unusual to pick a tool off the shelf and use it to solve a specific problem. The same does not apply when it comes to data.
SEE: Hiring kit: Database engineer (TechRepublic Premium)
You cannot simply plug in a data quality application and expect tangible upticks in quality unless you understand why you are doing it and how it works. Again, it’s a good idea to hire data professionals and trust them with the resources they need to make these tools do their jobs effectively.
Be aware of the effort required for new data projects
Once you know what you want to achieve with your data strategy and how it will impact the business, you need to ensure the structures and resources are in place to support it before you begin. It is common for data projects to be delayed for months while companies put in the requisite preparatory work they forgot about.
Encourage structural change to avoid data silos
I have seen firsthand the importance of involving the C-suite in data decisions, but communication about data strategy and projects shouldn’t stop there. Equally important is ensuring there is communication across all data stakeholders, so no information silos develop. Companies need to break down these internal barriers to make data projects succeed.
Becoming truly data-driven
As data continues to be generated in vast amounts and plays an increasingly important role in our lives, now is the time to consider how you can best utilize your existing data and generate new valuable data for your business and customers.
To be truly data-driven, organizations need to align their data and business strategies, utilizing the insights they find to set, drive and monitor their progress against objectives. This approach is sure to advance the business more quickly, allowing companies to offer better products and services that align with what their customers want.
Read next: Top data quality tools (TechRepublic)
Michael Queenan is the co-founder and CEO of consultancy-led data services integrator, Nephos Technologies. A decade ago, Queenan and his business partner, Lee Biggenden, identified a gap in the data market for a services-led integrator to guide the largest organizations through the complexities of data strategy, governance and analytics. As CEO, Queenan plans Nephos Technologies’ future strategy and direction, identifying trends 24-36 months in advance and building centers of excellence to deliver on those trends.
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