Ultimate Guide:
How To Turn Company Data Into Value


The Ultimate Guide on How to Turn Company Data Into Value

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Every company is saturated with data. Customer data, third part data, social media data, systems data, environmental data…we’re all swimming in a rapid river of information that’s bigger and churning faster than ever before. So how do you keep your head above water?

Some organizations let the data swirl around them and simply try not to lose their footing. Some pour their data into separate buckets and store the buckets in various locations, creating information silos.  

Leading organizations store, secure, and use data in ways that save money, add revenue, connect people, and improve their employees’ and customers’ experience.

Learn how to become a company that leads the way with data.

Here’s everything you need to know about the data landscape and how to transform the way you use it, from strategy to execution to governance. By following this guide, you’ll identify where you are in the data transformation process and learn how to take the next step toward data maturity.

Read on or use these links to jump ahead. Let’s dive in.

What is data transformation?

Data transformation is the process of systematically turning data into a company asset by fundamentally changing the way people and technology handle, store, use, and govern it. This process often includes:

  • Building or modernizing a data platform
  • Building a large storage system like a data lake or data warehouse
  • Connecting data across the organization
  • Adding innovative tech like AI or machine learning (ML) to automate tasks
  • Creating dashboards and reports to help leaders make proactive decisions
  • Improving data security
  • Creating a data governance structure
  • Engaging people in a new way of working with data

Data transformation vs. digital transformation

Digital transformation (also written as DX) is defined as “the adoption of digital technology by an organization to digitize non-digital products, services or operations. The goal for its implementation is to increase value through innovation, invention, customer experience or efficiency.”

The pillars of digital transformation are:

  • Digital Platform: Modernizing IT to become the digital backbone for a business
  • Intelligent Organization: Optimizing and advancing the existing business to create efficiency and value
  • Digital Products: Creating new business models, expanding markets, and acquiring customers
  • Experience: Engaging employees and customers to develop valuable relationships

Data transformation is central to digital transformation. An organization will face barriers to digital transformation if the business is not using data effectively to build their platform and optimize their business.

The importance of data transformation in 2023

Gartner recently released the top 10 strategic tech trends for 2023. From adaptive AI to digital immunity, it’s clear—to be able to scale, optimize, and pioneer, businesses must have a strong relationship with their data. In other words, to be a part of what’s next, you need to know what came before.  

We call that the Data Imperative.

The fact is, data consumption and production have skyrocketed. 90% of the world’s data was created within the last two years alone. When there’s so much data pouring into a company’s systems, it becomes more challenging to identify what data is valuable and what’s just noise. In addition, the more data an organization holds and the more hands that have access to it, the more risk there is for cyberattacks and information breaches.

90% of all the data in existence today was created in the last two years.

As the world become increasingly digital (maybe even moving toward the metaverse?), the pace of data production will continue to grow. By 2025, 463 exabytes of data will be generated every day. For context, some technologists say that all the words ever spoken aloud by humans equals about five exabytes.

Work functions that can be improved with data transformation

Clean, accurate data affects functions all over a business, including:

  • Accounting and finance
  • Compliance and governance
  • Customer service
  • Human resources
  • Research and development
  • Training
  • Sales and marketing
  • Technology stack
  • Quality management and quality control
  • Distribution and supply chain
  • Operations
  • Strategy and leadership

Basically, if it’s measurable (and business function should be), data transformation can make it simpler, more efficient, or more effective.

Common barriers to data transformation

On the surface, it’s easy to say, “Yep, data transformation is a good idea.” In fact, digital transformation is the top company initiative for 2023. At the same time, many organizations encounter challenges that sideline big change initiatives before they ever get moving. The top five barriers to transformation are:

  • Complexity of current environment/internal silos
  • Too many competing tech priorities
  • Security concerns and compliance constraints
  • Change management and implementation complications
  • Operating-model transformation complications (current business processes are too rigid)

In our experience, we’ve found that that customers usually fall into one of three camps.

  1. The organization knows they need to transform, but they’re worried about how much it costs to modernize their data platform.
  1. The org knows they need to transform, and they have a goal on the horizon, but they don’t know how to get there.
  1. The org has a plan for transformation, but they’re having a hard time getting people on board with a major change.

Don’t worry. We’ll touch on the case for each one of these scenarios later on.

The 3 truths of data:

Good data is an integral component of successful transformation for organizations. Whether your org wants to expand, create better consumer experiences, or simply shift away from siloed workstreams (hello, democratized data) – a solid data strategy will get you there.

So, how do you break through the noise to define what works? Start with the 3 data truths all orgs must know to understand why data is crucial to the success and growth of modern companies.  

  • Truth #1: Data is not a new idea, but its significance and scale are greater than ever before – and to more organizations (not just the big guys).
  • Truth #2: Harnessing the power of your data can massively impact your organization’s success. 
  • Truth #3: You must undergo a holistic data transformation.

When you harness the power of data, you plant the roots of scalable, innovative and adaptive transformation.  

Challenges of Data

The threat of lost revenue, security breaches and business inefficiencies rest upon the broken infrastructure and poor data strategy of organizations yet to adopt a holistic approach to their data processes. The future demands of data will require organizations to uncover their data inefficiencies and invest in the tools to optimize, grow and scale in a data first landscape.  

The top 3 data challenges businesses face are not unique to any particular industry. All organizations should consider the following challenges when building the framework toward data transformation.

  • Challenge #1: Data is scaling, faster and bigger.
  • Challenge #2: Data is growing more diverse, all the time.
  • Challenge #3: Data is disconnected. 

Roadmap to data transformation

To successfully navigate your orgs data terrain, a data transformation roadmap Is key to forging your path forward. The five steps to data transformation include:

  1. Strategize - creating a vision and strategy for the future of the org’s data

To effectively map a data journey, it’s important to pinpoint the specific processes needed to meet high-level goals as they apply to the collection, storage, and usage of company data. This means implementing a strategy for reliable and trustworthy systems that can be duplicated with confidence over the course of the journey to data transformation.    

  1. Capture - creating a digital data lake to capture data.

After creating a data strategy, companies can move on to accessing and storing the vast, diverse, and unstructured data available to and across the organization.

  1. Equip - equipping the business with data that enables progress.

Equip teams with the data they need to chase down the big-picture goals. The data landscape is vast, but the power of an educated team is limitless.    

  1. Integrate - integrating data to augment existing services, create new ones, and become an industry pioneer.

Data integration acts as the meeting ground for data pulled from various sources. As more and more new data flows into your organization minute by minute, integration cuts down on the time needed to prepare and analyze data, and contributes to overall data continuity.    

  1. Govern - creating a data movement in your organization

When it comes to managing data, organizations must contend with a range of regulations, security initiatives, skill gaps, and budget constraints. To ease your employees into a truly data-driven company culture, training is key. If your employees recognize the benefits of adopting data-centric practices for both themselves and the business, success is more attainable.

What is a data lake?

Beginning a transformation requires creating a vision and strategy for the future of the org’s data. The next step is collecting all the vast, disparate data that flows into and around the organization in one place. Captured, centrally located data is data that can be used everywhere in a business instead of being siloed and segmented across departments. The ability to store it unparsed and draw exactly what is needed, when it’s needed, has brought about industry-shattering products like Uber and e-libraries. And that ability comes from data lakes.

What is data governance?

On the data roadmap, governance means managing data and engaging people. While both elements appear in earlier steps—you can’t build a data strategy without understanding how your people want to use your data, for example—governance is the final maturation of technology, policies, and people management.

Here are the five key factors to building good habits that will generate momentum once your data governance program is underway:

  1. Impart a sense of urgency for the program.

Once an organization devises a plan to manage its data assets, there must be a sense of urgency to keep the plan in place.

  1. Communicate, communicate, communicate.

The cornerstone of a successful data governance program is a well-organized, cross-departmental communication plan. A solid plan helps remove the silos and maintain company-wide support for the initiative.

  1. Operationalize change within the organization.

The goal is to learn what works within the organization early on, to ensure the data management team delivers value quickly and that the process is sustainable moving forward.

  1. Make the plan as RACI as possible.

Active listening—to supporters and detractors—and including a RACI (Responsible, Accountable, Consulted, Informed) model in the change plan helps everyone on the governance team understand their roles and responsibilities throughout the process.  

  1. Measure, share, and repeat.

Organizations can’t manage what they don’t measure. Documenting and implementing KPIs (Key Performance Indictors) to measure the initiative’s progress over time helps connect pieces that may not obviously be cause and effect.

Results of data transformation with examples

People often ask, “What’s the ROI for digital transformation?” Given the investment required, it makes sense that a business would want to see some proof of results before undertaking modernization and transformation projects.  

Here are a few quick stats:

  • Companies with digital-first strategies are 64% more likely to achieve their business goals than competitors
  • The top benefits of adopting a digital model are it improves operational efficiency (40%), allows for faster time to market (36%), and helps meet customer expectations (35%).
  • 56% of CEOs said that their digital improvements have already improved their profits
  • Digitally mature companies are 23% more profitable than their less mature peers
  • The top benefits of adopting a digital model are it improves operational efficiency (40%), allows for faster time to market (36%), and helps meet customer expectations (35%).

Remember, there’s no digital-first models without data-first processes. Following the data roadmap is how an organization positions itself to join the leaderboard of digitally transformed companies.

Examples of data transformation

From high tech to high finance and from healthcare to hospitality, leading organizations have prioritized data initiatives to transform their tech stack, sales, employee satisfaction, and customer experience.

Data platform for a global footwear brand

This client is a global retailer of athletic apparel consisting of ten distinct brands and over 3,000 stores across dozens of countries, plus mobile and online shopping experiences. They were undergoing a large-scale digital transformation initiative, driven by the desire to create a frictionless and consistent customer experience across all channels and brands.

By the end of the project, the client company had a foundational data platform that would meet the scaling and diverse business needs across their various brands. This data transformation increased online sales by 30% and implemented scalable infrastructure that can dynamically support up to 3x the expected customer traffic.

Data visualization in an industry report

Here’s a fascinating example of using data to create value for potential leads. In an industry report, TekSystems included this interactive data visualization that allows readers to explore the extent to which companies in a similar industry, size band, or location as their own have digitally transformed. This is a clever use of TekSystems’s research data because it provides instant value to readers, shows off the company’s ability to display data in an insightful way, and creates a memorable touchpoint.

A construction company that uses the past to build the future

Teichert, a heavy civil construction giant based in Sacramento, has been building California for over 135 years. Clearly, this company understands how to be successful in a changing world, and according to President Mary Teichert, “We have been a technology company from day one.” Recently, they partnered with Launch to build InQuarry, a data platform that creates a “network of knowledge” based on historical estimation and project management data.

This data platform provides a digital assistant for all of Teichert’s work. It helps them put together better bids, so they win the jobs they want. It helps their project managers execute the jobs more effectively and puts up a flag when it senses an inefficiency or impending issue. Most importantly, it pools the expertise and knowledge of all their people from all Teichert jobs.

Interested in learning more? Teichert leadership recorded a podcast episode about what they’ve gained from data transformation—listen here!

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Advertising Data Portal for Global Telecom Business

This media and telecom giant had a vision: a brand-new division that would make a billion dollars in the first year alone. They wanted to become a leader and innovator in the new direct-to-consumer advertising trend. With 70% of American households using at least one of their products, they saw a lot of opportunity to revolutionize ad delivery, curating ads down to each individual household.

With guidance from Launch, they created a brand-new advertising data portal that provides real-time insights to advertisers and enables intelligent decision-making around advertising spend.

The client had planned to make a billion dollars in this new revenue stream in the first year. Turns out, it made $2 billion in the first year. And the initial version of the advertising platform went live within a mere 5.5 months.

Learn more in this case study.

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Over to you

Data transformation isn’t easy. It takes a combination of tech, process, strategy, and most importantly, people. But in this digital age, being able to capture, use, and govern data in a secure and robust way is what will make you a leader and not a laggard.

So, now it’s your turn. How can you use the power of data to move your organization from now to next? If you’d like a hand in determining what your next steps to data transformation are, we invite you to take a Launch Future State of Data Workshop. In just a couple hours, you’ll leave with a vision plan for the next 1-3 years of your data transformation.

Future State of Data Workshop

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