The Real Deal for Transforming Data into Business Value

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The Real Deal for Transforming Data into Business Value

Heather Holst-Knudsen

In today's marketplace, data is more valuable than ever before. Businesses that use data analytics and AI to inform and support their decisions often outperform their competitors who rely on gut instincts alone. A recent HBR Pulse survey on transforming data into business value through analytics and AI found that 75% of respondents say having a data-driven culture is critical to their organization's overall success. But, where is your go-to-market source of truth? How can you ensure that the data you are using is accurate and up-to-date? In this post, we'll explore the survey results and discuss some effective strategies for transforming data into business value.

Unified Source of Truth in the Cloud

The survey found that organizations already highly data-driven before the pandemic doubled down and became even more data-driven while struggling organizations fell further behind. Leaders in the survey invested in and accelerated data, analytics, and AI initiatives at higher levels than their counterparts. The reason for this is obvious: with COVID-19 completely transforming how businesses operate in weeks, executives were more inclined to adopt data-driven cultures and accelerate industry-specific solutions, including AI.

In addition, it was discovered that having a unified data cloud is important for organizations that desire significant value from their approach. A Unified Cloud approach enables businesses to share data more efficiently and effectively, increasing collaboration and reducing redundancy, resulting in the ability to identify opportunities for innovation, market entry, competition, scale efficiency and agility, reduce risk, and improve operating margins.

The Challenge and Critical Need for Data Democratization

“While it appears that many companies have their data management acts together, in fact, many don’t,” says Doug Levin, executive in residence at Harvard Business School and lecturer at the Harvard Business Analytics Program.

However, the survey found that organizations still struggling to keep up often face challenges in analyzing data across multiple sources and data quality issues. In the past, data silos have been creating barriers to analyzing data across the whole corporation and restricting access to real-time data. Sourcing data from various places remains challenging, including complexities in integrating/consolidating data from several systems/sources. Additionally, data quality issues often arise from poor data governance practices.

Multicloud adoption is emerging as a popular solution, but it presents challenges in data governance/management and service integration and management. However, democratizing access to data and analytics tools and AI capabilities is key to remaining competitive.

Bye Bye Data Chaos, Hello SOT in the Cloud

Organizations with data complexity due to high levels of daily transactions, mergers and acquisitions, diverse customer segments, and revenue streams have even greater challenges.

CRM and data warehouses are used for data management, but they are not well-suited for most B2B organizations. For instance, a CRM cannot handle detailed digital data such as product analytics, payment/booking/subscription information, call intelligence data, among other areas. Moreover, data warehouses limit you to high-level dashboards that provide minimal insights, or you have to hire a data science and engineering team that can translate the data into valuable insights. Organizations in highly transactional environments with multiple revenue sources and customer segments such as business information, media, events, and marketing platforms require more innovative approaches to data management and reporting.

Now organizations can use end-to-end data management and advanced analytic solutions such as Insightify. Insightify sits on top of core systems such as CRM, Marketing Automation, Finance, Operations, CDP, and even existing business intelligence tools and seamlessly aggregates data from decentralized sources, unifying it into a Single Source of Truth (SSOT) at the platform level. Insightify preserves data in its original format at its source so that businesses can avoid the high costs and risk levels associated with waterfall-level data transformation projects.

Using this unique approach, users are empowered with high-level dashboards and visualization tools coupled with in-depth drill-down capabilities to diagnose, interpret, and prescribe actions and decisions.

Measuring Financial Returns

Finally, the survey highlights the importance of measuring and reporting data and analytics investments, business value, or outcomes. Investing in data and analytics is only useful if it can deliver concrete business outcomes, such as new product/service introduction, operational efficiency, customer satisfaction, revenue, and market share. Leaders' organizations reported improved performance in each of these key areas. Maximizing business value from data requires leadership support and enterprise-wide strategies for data and analytics.

In conclusion, organizations that prioritize their data analytics initiatives can expect significant returns. With data-driven cultures becoming must-have requirements for modern-day business, businesses must ensure they have a significant head start over their competitors. Leaders who invest in data, analytics, and AI initiatives position themselves to address the effects of disruptions while driving innovation effectively. The right approach, using the correct data from the right platform, can create significant business power. Organizations that utilize effective strategies for transforming data into business value can improve their operational efficiency, customer satisfaction, revenue, and market share while also 21differentiating themselves from their competitors.

About the Author

Heather Holst-Knudsen is a distinguished figure and expert in the events, media, marketing and technology sectors. Using her extensive experience, she guides clients in adapting to structural economic and market changes, seizing the chance to innovate and evolve. She specializes in digital and data disruption and opportunity, exploring how these overarching factors can impact revenue growth, customer-centricity, operational efficiency, profit margins, and the overall valuation of companies in both public and private markets.

Her journey began at her family business, Thomas Publishing Company, where she honed her skills. She further expanded her expertise by holding positions at early industry giants Miller Freeman, Reed Elsevier, and IDG. Returning to Thomas Publishing, Heather founded and spearheaded Manufacturing Enterprise Communications, an integrated media portfolio connecting buyers and sellers in the manufacturing and technology sectors. Starting in 2015 and spanning the next seven years, she leveraged her expertise as a revenue and business leader in various SaaS businesses, including Feathr, Gleanin, Brella and Edflex.

Heather is deeply passionate about digital innovation, data monetization, and AI and how these strategies fuel revenue growth, profitability, and company valuation. To serve and create value for clients in these areas, she launched H2K Labs, dedicated to generating and leveraging value through data for media, business information, events, and adjacent technology and service markets.

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The Real Deal for Transforming Data into Business Value

The Real Deal for Transforming Data into Business Value

Unified Source of Truth in the Cloud

The Challenge and Critical Need for Data Democratization

Bye Bye Data Chaos, Hello SOT in the Cloud

Measuring Financial Returns

About the Author

Popular

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