Agility, Growth, And The Data Warehouse

Neil McGovern

Increasingly sophisticated and demanding customers are driving businesses to evolve agile, Big Data-friendly data warehousing and analytics environments. Businesses are learning that being agile is not optional if they want to keep up with rapidly changing technologies, competitor initiatives, and customer needs. Plus they need Big Data capability in order to manage the many different varieties of data, and the large and growing datasets, that contain the insights that can drive effective responses to these changes. Solutions that effectively combine agility and Big Data are what Forrester calls “systems of insight.”

To provide a better understanding of how businesses are leveraging these systems in a rapidly changing landscape, Forrester surveyed nearly 300 business and technology decision-makers from around the world. The survey results reveal a strong link between agility and success when it comes to implementing business intelligence (BI) solutions. The lessons learned from this research have a lot to tell us not only about BI, but about data warehousing and analytics overall.

Agility = Growth

The key finding from the survey is an unmistakable link between business growth, agility, and a focus on turning data into insights and insights into action. While some businesses struggle with establishing the ROI of their data warehousing and analytics initiatives, the research shows that high-growth, agile businesses deploying successful solutions are also those who have the clearest understanding of that solution’s ROI proposition.

Agile organizations are high-growth in part because they are better at dealing with the kinds of problems that typically slow businesses down when implementing new technologies and/or business models. When deploying a new data warehousing solution, agile organizations gravitate towards more open and resilient technologies and practices, leading to fewer problems with:

Processes. Agile environments facilitate easy platform migration and implementation while ensuring data quality, providing structures for governance, and eliminating information silos.

Costs. As noted above, high-growth, agile businesses have a clear understanding of what their IT dollars are buying them. In fact, 94% of the businesses fitting this profile, “have a well-established methodology for measuring…ROI…and creating…business cases with tangible business benefits.”

Technology. Agile solutions focus on simplifying and accelerating scalability, data quality, latency, and managing operational risk.

People. Agile organizations avoid the common pitfalls of lack of knowledge, lack of training, cultural clashes, lack of ownership, lack of top-down sponsorship, and lack of alignment between IT and business.

Avoiding problems is all very well, but the survey shows that the most important benefits from implementing an agile data warehousing solution take the form of significant enhancements to how the organization turns data into insights and insights into action. These include:

More effective analytics. An agile data warehouse helps the organization to evolve from reporting and historical analysis to more advanced, predictive analytics. It also supports incorporating new data types and structures into complex behavioral models that produce a level of understanding previously unavailable.

Faster project turnaround times. Introducing whole new data sets from new data sources, which can take weeks or month to properly integrate into the data warehouse and overall analytics workflow using conventional approaches, can take days or even hours with an agile data warehouse.

Empowered business users. And agile data warehousing solution puts data and analysis into the hands of those who need it by facilitating open-ended data discovery and self-service analytics.

Keys to going agile

Businesses looking to implement an agile data warehouse need to be aware that agility derives from the right combination of business practices and technical capability. The research shows that businesses that have successfully implemented agile solutions are those that have focused on a few key principles:

Move to real-time solutions. One of the biggest transformations occurring in business today is the death of waiting. Businesses can no longer tolerate latency in their systems or processes, especially if their customers (or their competitors) are already operating in an environment that assumes those delays are gone. Business need to ingest, analyze, and act upon data instantaneously, and their processes and systems must reflect that reality.

Build incrementally. Forrester warns that “big bang approaches, including legacy enterprise data warehouses, have a low chance of success.” Rather than trying to fix everything at once, the more reasonable and nuanced approach is to make the transformation in phases. Start with the systems and infrastructure and then build new processes on top of them. True agility is more likely to emerge gradually than it is to magically appear.

Ensure business ownership. While IT will generally continue to own the infrastructure that supports an agile data warehouse, the business owns the results that the new solution must provide. Ultimately, agility is a problem that the entire organization must solve, and the business must take the lead.

Realign IT priorities. In the era of the agile data warehouse, IT takes on a new and very different role. “IT pros are no longer responsible for building reports and dashboards. Instead, they empower their business peers with self-service tools, platforms, and applications, enabling them to get their own insights and turn these insights into action.”

And finally…

Invest in what works. As the earlier section on ROI suggests, agile businesses tend to grow rapidly, in part because of their clear understanding of what return they are getting on the investments they make in technology and process. Businesses that are broadening the scope and the reach of their data warehousing and analytics solutions, and that are working to ensure these solutions remain agile and resilient, will continue to reap the rewards of better alignment, better performance, and accelerated growth.

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Neil McGovern

About Neil McGovern

Neil McGovern is a senior director of Marketing, SAP HANA, at SAP. Drawing on his 25+ years of experience in the software industry, Neil is responsible for product marketing for SAP Internet of Things strategy and the SAP HANA business data platform. In addition, Neil focuses on high-performance analytics for risk, trading, and compliance and has presented at conferences around the world on the latest trends and technologies required for cutting-edge performance in capital markets. Prior to SAP, Neil was VP of Engineering at New Era of Networks, and CTO of Convoy Corporation, where he was a pioneer in the enterprise application integration market. Neil has a degree in Computer Science and an MBA.