Data As an Asset- How to Leverage Technology to Monetize Your Data?

Data As an Asset- How to Leverage Technology to Monetize Your Data?

Clive Humby, a British mathematician, is known to have coined the phrase “Data is the new oil” way back in 2006. Back then, the analogy could be well understood because oil at that time was one of the most coveted commodities in the world. Since then, it has generated a lot of discussion in the context of the Fourth Industrial Revolution (I4.0).

Like oil, data is worthless unless it’s captured, processed, and consumed. Similar parallels can be drawn out if one attempts to give data assets a valuation. The analogy falls short at this point as oil is a finite resource whereas data continues to be generated by operational transactional databases, connected devices, machines, website and application logs, etc.

This turns the traditional supply-demand view of economics on its head. If you have an exponentially growing supply of a resource with relatively lower demand, this traditionally will drive the price or value of the resource down.

In the data world, this couldn’t be further from the truth. It is the correct combination of data assets manipulated with purpose in a very specific way that can and will provide exponential value to its stakeholders.

In this sense, I would propose that a better analogy would be comparing data value to the movie ‘The Matrix’ where the world is fully digitized and can be viewed as a stream of symbols scrolling down a screen by the ‘real world’. Value can only be realized when the ‘real world’ stakeholders can plug into the stream and manipulate the digital world.

In this blog, we will give a point-of-view as a technology systems application provider (Data-Sage), and a business and digital transformation service provider (Neo NextGen) touching on 2 broad topics:

1. What are the main friction points to the adoption and scaling of an industrial data initiative?

An industrial data initiative is a highly complex series of technology transformation projects that are required to lay a foundation from which data value can be derived. At Data-Sage, we deploy a ‘5 stage of readiness’ questionnaire to simply assess our customers’ readiness along the lines of People/Culture, Process, and Technology.

Friction points can exist in all 3 aspects and need to be addressed in specific ways depending on the state of readiness of the organization. If the foundational layer of any of these 3 is not set, odds are slim to none that an organization will be able to derive value from data assets.

Symptoms of organizations stuck in pre-foundational in either People/Culture, Process or Technology include having undergone many Proofs-of-Concept that cannot scale, overspending on a data transformation in terms of time and money, etc.

People/Culture Friction Points

On the People/Culture side, the main friction points typically occur when there is no enterprise-wide, formal data strategy that is driven from the top. Complete, personal, and visible ownership from the Senior Executive driving the data projects is required.

The leadership needs to show signs of personally going through the data projects and enabling execution teams and partners to get past roadblocks. There is also a lack of data engineering talent capable of executing large-scale data initiatives. This is where technology partners can help accelerate the roadmap.

Process Friction Points

On the process side, the number 1 friction point, especially in asset-intensive industries, is that there is no set data governance model or even a master data strategy.

For industrials that are used to designing, producing, and maintaining a physical asset as a business, the importance of correctly managing data assets is not natural. A symptom of this is when most of the business units go outside of enterprise systems in Excel files or non-connected tools to perform their day-to-day functions.

Technology Friction Points

On the technology side, more often than not, there is no easy way for business units who want to derive value from data to access and consume their data the way they need it.

Business units often have to wait weeks or months for a report or access to data required for them to respond to market conditions whereas a well-architected enterprise data system should be able to respond to needs within minutes and be self-serve.

Challenges in Industries with Deep Content Knowledge

Finally, many industries, such as aerospace are particularly challenging to transform due to reliance on deep content knowledge and expertise. Business sponsorship, adoption, and change management from all stakeholders are key components of any successful transformation. This can be especially important to ensure that the business will continue to prosper.

Creating a Culture of Transformation

A successful transformation starts with education and empowering a mindset of acceptance to change. Management is encouraged to create healthy competition by implementing incentives, career advancement opportunities, and celebrating high-performers which inevitably fosters a culture of engagement.

By designing an atmosphere of communication and partnership, the organization works together to create longevity for the business.

Digital transformations have become a core factor of the employee value proposition, it augments the employee experience and attracts new talent.

2. What are the top use cases and how to match an industrial data ops investment to a broader technology roadmap?

Some of the top use cases in an industrial data ops investment that we’ve seen revolve around 3 major concepts:

Achieving Operational Excellence in the Digital Era

Achieving competitive advantage through streamlined operational excellence from design to production, all the way to aftermarket. Simply put, technology is evolving so quickly, businesses must transition to digital platforms to stay relevant, and individuals need to do only what they can do, elevating to more intelligent work across the board. This in itself unlocks profitability and value creation.

Delivering a Digitally Enhanced Customer Experience

Offering a differentiated customer experience with a more digitally enabled product or production cycle. This includes a digitally native way to interact with the company. Today’s consumer expects a digital platform to stay connected with new and existing offerings.

Creating a Digitally Enabled Culture for Talent Retention

Attracting and retaining talent by offering a unique and digitally enabled work environment. It is very important to create a culture of development and learning from within.

Digital transformation has become part of the employee value proposition, engaging a younger generation that may otherwise have more interest in eVTOL (Electric Vertical Take-Off and Landing vehicle), drones, blockchain, and other engineering opportunities outside of traditional aerospace and other industries.

Final Thoughts on Data As an Asset

In terms of matching an industrial data ops investment to a broader technology roadmap, the challenges remain the same as any digital transformation initiative. Since the intrinsic value of data assets is inherently difficult to quantify, CxO’s struggles with the business case to start and scale these types of investments.

In our experience, the companies who have successfully implemented a broader Industrial Data Ops investment and achieved their returns have started by investing in the planning and the foundational layer.

The ROI-Return on investment of this foundational layer is not evident until specific use cases are enabled. Some of these transformations take multiple phases over multiple years depending on the complexity of the legacy systems, processes, and culture therefore it is imperative to keep these end-use cases in mind all while setting up the proper foundations for data ops enablement.

Both Data-Sage and Neo NextGen recommend agile methodology as well as proof of concepts – to allow companies to test the best mix of technology to solution at minimal cost to ensure a tried and tested approach before launching into high-priority digital projects.

Who Are Data-Sage & Neo NextGen?

Data-Sage is a leading data engineering and analytics company that has been helping large enterprise customers accelerate their digital transformations through establishing data strategies and implementation plans. They have earned recognition for their expertise in designing business intelligence platforms.

Neo NextGen is a renowned provider of business and digital transformation services, from strategy to operations, with a focus on sustainability, unlocking incremental value, centered on an ethos of people, productivity, and profit. Aerospace transformers powering digital workflow.

Thanks for reading our thoughts on data as an asset and stay connected to get more like this.