Why becoming data-driven might not be enough

Data Analytics

Date : 03/11/2022

Data Analytics

Date : 03/11/2022

Why becoming data-driven might not be enough

Gain insight on how insight-driven organizations embed analytics capabilities and establish a link between growing data volume and business value encouraging data monetization

Soumendra Mohanty

AUTHOR - FOLLOW
Soumendra Mohanty
Chief Strategy Officer & Chief Innovation Officer

Img-Reboot
Like the blog

Table of contents

Why becoming data-driven might not be enough

Table of contents

Why becoming data-driven might not be enough

Img-Reboot

Becoming a data-driven organization is game-changing — the more data you process, the more you improve your products and services, and the better you serve your customers and markets. The resulting data, in turn, improves products and services and helps shape demand and new growth models.

Ideally, the exponential data and technology advancements we’ve experienced in the last few years should have catapulted organizations’ ability to deliver significant business value continuously. A Forrester report highlights this contrast, that despite data abundance, the underuse of analytics is costing companies dearly. The ground reality is that a majority of organizations are stuck in the limbo of “trapped value,” the gap between their current and potential value from data. Unable to close the gap, companies miss out on the massive opportunities of data-led growth supported by operational efficiency, smarter strategic decisions or product/service innovation.

This is why being data-driven shouldn’t be the ultimate goal. Think about it. Data inform better decisions, but to drive action with data, we must create a continuous pipeline of questions about the next steps. In other words, we should be constantly seeking “the next” pivot.

The distinction is subtle: Do you start with data and then find a purpose, or do you start with a purpose and then find the right data?

Researchers Bart de Langhe and Stefano Puntoni suggest that instead of finding a purpose for data, we should find data for a purpose. This approach is called insight-driven thinking and is the cornerstone of insight-driven organizations.

Data on hand leads us to the false complacence of owning a powerful asset. Consequently, we start tasking our data analysts, data scientists, and business SMEs to find ways to extract value from this data. We get carried away by preferences, pre-existing beliefs, and tribal knowledge bias, in our rush to prove ROIs based on narrow data-led solutions.

This pitfall requires a different strategy. Through interconnected, ongoing initiatives that operate within and between business edges and timeframes, companies need to subscribe to a “two-speed” approach: Invest in re-imagining today’s core businesses while designing and executing a carefully choreographed transition to the next pivot.

Being data-driven is sufficient for the first. But to stay ahead of the disruptions and continuously prepare for the next pivot, businesses must become insight-driven.

How To Become An Insight-Driven Organization

Becoming insight-driven has a two-fold impact: It releases both current and trapped data value. Over the past decade, organizations have increasingly made significant investments to become data-driven. Unquestionably, there’s enormous potential for building products and service offerings around strong data foundations. But to derive value from data, a mindset shift to becoming insight-driven must be embraced throughout the organization. Here are three important steps to get you started:

  • Institutionalize the approach of questions first, not data first. Starting with a questions-first approach ensures that you don’t take the story data is telling you at face value. With this approach, you’re exploring the width of processes end-to-end to probe their intrinsic value and discover larger connected problem spaces. The key is to design and validate questions with business owners iteratively. The surprising effectiveness of this approach may lead you to realize that you may not have all the data required to explore these problems and opportunities. In contrast, if you start with data first, you will quickly go deep and narrow, creating solutions for only one silo of the process value chain.
  • Establish a methodology for your teams to explore the unknown more than the known, and incentivize them for coming out with a list of viable best courses of action. Transforming from a data-driven organization to an insight-driven one requires a well-designed methodology. Start by outlining the key objectives of your business and how insights can help achieve them. How can you level up with product and service innovation? Can you define clear pathways from business decisions to data sources? How will you enable and reward your teams to think unconventionally and discover wider problem spaces rather than come out with single-node solutions? How do you keep them from going down the path of “forced inventions,” littered with the possibility of biases and preferences? Enforcing a strategic framework enables you to overcome organizational boundaries and inhibitions and integrate people, processes, and platforms along with the defined purposes for maximum ROI. As organizations begin to realize the competitive advantage of such a framework and the contributing teams are rewarded, a culture forms around going wide first and then narrow. This snowballs into better outcomes until this strategic framework becomes the new way of doing business.
  • Set up an ecosystem where you can collaborate easily with all stakeholders (internal and external). The insight-driven mindset questions the underlying assumptions in any process and helps businesses make strategic decisions taking the bigger picture into account. It embeds questioning, analysis, data, and reasoning into the everyday decision-making process. Collaboration and co-innovation become the key in such organizations to making better decisions and driving sustained innovation. And analytics projects, though they start small, will quickly scale to take enterprise-wide scope for greater business impact in such organizations. A closer look at insight-driven organizations uncovers an interesting advantage. They’re able to apply a questions-first philosophy everywhere in their businesses. Once in a while, the questions themselves become bigger initiatives worth pursuing. In summary, while truly insight-driven organizations are built on data and insights, it requires a delicate play of the following measures:
    • Embedding analytics capabilities across the organization, building insight delivery into everything from workflows, systems, and applications, to other core business processes.
    • Establishing an organizational culture of exploration and discovery rather than just blind trust in data on hand, by motivating employees to ask bold questions.
    • Making insight-driven decision-making a grassroots capability amongst all employees rather than limiting it to an executive-level capability.
    • Establishing a clear link between growing data volume and measurable business value to encourage data monetization.

Insight-driven organizations are identified by their innate ability to ask questions and drive the insights advantage in smaller situations that culminate into bigger outcomes, creating a flywheel effect.

This article was originally published on Forbes.com

Soumendra Mohanty

AUTHOR - FOLLOW
Soumendra Mohanty
Chief Strategy Officer & Chief Innovation Officer

Topic Tags


Img-Reboot

Detailed Case Study

Driving insights democratization for a $15B retailer with an enterprise data strategy

Learn how a Tredence client integrated all its data into a single data lake with our 4-phase migration approach, saving $50K/month! Reach out to us to know more.

Img-Reboot

Detailed Case Study

MIGRATING LEGACY APPLICATIONS TO A MODERN SUPPLY CHAIN PLATFORM FOR A LEADING $15 BILLION WATER, SANITATION, AND INFECTION PREVENTION SOLUTIONS PROVIDER

Learn how a Tredence client integrated all its data into a single data lake with our 4-phase migration approach, saving $50K/month! Reach out to us to know more.


Next Topic

Five imperatives for the modern Chief Data Officer



Next Topic

Five imperatives for the modern Chief Data Officer


0
Shares

24581
Reads

Ready to talk?

Join forces with our data science and AI leaders to navigate your toughest challenges.

×
Thank you for a like!

Stay informed and up-to-date with the most recent trends in data science and AI.

Share this article
×

Ready to talk?

Join forces with our data science and AI leaders to navigate your toughest challenges.