Why Data is a Strategic Asset in your Digital Journey

By Vikram Chalana on Jul 6, 2017

In the last few articles, we talked about enterprise applications — data related challenges and solutions to these challenges. In this article, I’ll discuss the technology trends shaping the industry today that are leading to data becoming even more important in these applications than ever before. I’ll also talk about the increasing importance of data quality and data governance.

Technology trends shaping the industrydata governance

Every business today, large or small, across industries from manufacturing and retail to education is being disrupted by fundamental shifts in digital and data resources. Companies that successfully adapt to these transformations and implement policies to treat data as a strategic asset will emerge as the leaders of tomorrow. They’ll be able to trust their data and leverage that data to obtain strategic insights. They’ll also empower business teams to outrun their competitors by shortening their business cycles. Companies that can’t leverage data effectively run the serious risk of being left behind.

Digital transformation has been one of the biggest recent trends, driven largely by e-commerce and mobile apps. Retail and financial services are ahead of other industries in leveraging e-commerce channels and providing an improved customer experience through mobile apps. Companies in other industries are also increasingly showing interest in participating in this digital revolution.

Digital transformation often involves engaging in a digital business. This can offer new revenue channels, like e-commerce or mobile apps. Digital business can also lead to new products and services where data and analytics produced in your business can be sold as a service.  Digital business can ultimately change how and what your company sells and who your company sells to, and data is the fuel for digital business.

Another trend that’s emerged involves analytics. This is the ability to carefully examine data and identify business changes and trends that your competitors can’t foresee – and this gives you unique insights and a better sense of where things are heading.  Recent research by Keystone Strategy finds that companies who are able to apply sophisticated data and analytics capabilities as a regular part of their business enjoy an operating margin 8% higher than other organizations. This translates to almost $100M in average operating profits for those organizations!

Data quality and data governance

All initiatives that involve digital transformation — big data, analytics, machine-to-machine, and machine learning — rely on having high-quality data. Beautiful analytics dashboards can only be produced if the underlying data is good. If you feed a predictive algorithm bad data, it will lead to bad outcomes. As companies come to this realization, they’re starting to build core data management disciplines to improve data quality.

Some companies have tried to address data quality after the fact with data lakes and data warehouses, but data warehouses are highly problematic for real-time decisions and on-demand analytics. Real-time decisions require enterprise application data that are correct the first time, which means companies need to be proactive about resolving data quality issues.

Most organizations don’t have any data governance processes in place. For example, when it comes to managing customer data, many companies allow anyone in the plant (or even someone in sales) to add or update a customer account without following any clearly defined rules. To improve data quality, companies should set up data processes, identify ownership of customer data, and assign customer numbers to be used throughout the enterprise. This doesn’t mean data quality issues can be easily fixed by throwing tools at the problem. Tools are very helpful and necessary, but there needs to be an overarching data governance framework pertaining to data ownership, data decision making, data lifecycle, and data governance. This should take place at the enterprise level with the appropriate business leadership. The results of this activity, along with the implementation of important business-friendly tools, will drive a high-quality landscape in your company’s data environment.

Data governance often starts as an initiative within a single department to solve a specific problem. Your initial governance processes may be limited to critical data objects in your enterprise systems while you address fundamental changes in one or two areas in the organization.  If you want your data governance initiative to sustain itself over time, there needs to be a leadership-driven focus on how the organization works with data.

About the author

Vikram Chalana

As Winshuttle's Chief Technology Officer, and Co-Founder, Vikram has been focused on empowering people to transform their ERP-based businesses since Winshuttle's humble beginnings. He is passionate about technology that allows people to improve their lives and the way they run their businesses. Outside of work Vikram likes to spend time outdoors running, hiking, kayaking, and skiing.

Questions or comments about this article?

Tweet @Winshuttle to continue the conversation!