Competitive Edge: Harness The Full Potential of Business Data

Every business constantly faces the challenge of making critical decisions that shape its future. Until about a decade and a half ago, many leaders have heavily relied on their intuition and experience to make these decisions.

Then, the world took notice of the rise of tech companies like Apple, Amazon, Google, Meta, Microsoft, Netflix etc. Call it inspiration or jealousy, you had just one question — What made them so successful and influential? One key thing was they made decisions based on the abundance of data available. They still do.

They showed being data-driven is no longer an option but a necessity for sustainable growth and long-term success. Now, almost every company accumulates massive amounts of data due to its importance in decision-making. However, many still can’t leverage the full potential of the data they collect.

Organizational Transformation

NewVantage Partners conducts a Data and AI Leadership Executive survey every year. From their 2023[1] survey of C-level technology and business executives:

• Just 23.9% of companies participating characterized themselves as data-driven
• Only 20.6% say they have developed a data culture within their organization
• 79.8% of them cited organizational receptivity to change and business transformation as the greatest obstacle to realizing business value through data
• 93.9%, however, are planning to increase their investments in data in the wake of potential economic uncertainty
• 1.6% cited building data literacy as their top investment priority
• Only 23.8% report they are doing enough to ensure responsible and ethical use of data within their organizations and the industry

These alarming results are from executives representing giant Fortune 100 corporations such as Hewlett-Packard, JP Morgan Chase, Pfizer, Best Buy, etc.

There’s a great chance you work at a company where transformation tends to move slowly. Good for you, if it’s relatively quick.

How can you channel the full potential of your data and gain a competitive edge in the market? Recognize data as an information asset.

Data is a differentiator

The data you ethically collect, create and analyze differentiates you from your competitors.

There’s plenty of evidence of organizations using data to improve their products, build new ones and grow the company.

Netflix collects vast amounts of data on your viewing habits, preferences, and interactions to make data-driven decisions on what content to acquire, produce and recommend to you. You end up engaging with the content and being satisfied because it’s tailored to you. So does Spotify.

In addition to personalized recommendations, Amazon and AirBnB use data to improve accuracy of search results and offer competitive prices to drive customer loyalty.

You could say “I collect petabytes of data and run analytics too. What makes them so good?”

Being data-driven

They utilize data across all levels within their company to make decisions that successfully:

• Improve experience of customers using their products/services
• Accelerate revenue growth
• Limit risk
• Make operations more efficient

So, data is at the heart of most of their decisions that’s driving at least one of the above results successfully.

There are reasons why more than 75% of the survey participants say they haven’t created a data-driven company yet. It requires a lot of people with different opinions and areas of expertise to change the way they operate and make decisions each day. This is no quick-fix.

So, any potential fix is difficult to execute and only yields benefits long-term when successful. You know what is easy? To just write about the fix.

Having listened to tens of leaders in the data landscape, I observed three common themes when they talk about making data-driven decisions to successfully grow a company:

• Does the data strategy connect to the business strategy?
• Is the data architecture right to deliver the data strategy?
• Is there decent cross-organizational data literacy?

Data Strategy Is Connected to Business Strategy

Your fellow leaders, business stakeholders and you must look at data as part of the business. Not as a separate entity. In other words, you must see the strategic merits of data in achieving business goals.

As a result, the data strategy is managed, supported, and monetized alongside the company’s business strategy.

You have to first assess the current state, then, define the target state and finally manage the skills across teams.

Assessing the Current State

You need a good understanding of how data flows (or doesn’t) between various areas within the company like product/service, finance, HR, sales and marketing etc. This helps maintain data consistency, security, privacy, and governance across the company.

The next step is to identify the outdated data architecture, integration and management workflows that don’t align with business strategy.

This can look like lack of clarity in business objectives, insufficient scalability, inadequate governance, misalignment with tech stack, or among stakeholders.

Assessing the current state allows changes to the company’s current tech ecosystem to achieve business outcomes using data, analytics and AI.

Defining Target State

You must define the target tech ecosystem that’s ideally efficient, manageable, governed, secured, and flexible as business processes change. One day we’ll live in this ideal world!

This is also an opportunity to create a knowledge catalog that allows employees to access, curate, categorize and share data. Sharing knowledge assets, and compliance information is an effective way to centralize relationships between different business units.

Managing Skills In Teams

Members of the data teams need to have the skills to implement the strategy their leaders envision.

This includes acquiring talent from outside the organization, moving talent across business units, and re-skilling employees based on business priorities.

The idea is to define use cases, hire/re-skill employees and empower them to meet business goals.

In a post COVID-19 world, both you and I know that companies aren’t shy to let people go. #layoffs

Data Architecture Delivering Data Strategy

Value creation should be the primary objective of the technologies/tools you select. Not the popularity of tools. You create business value by identifying, capturing, and delivering the right data at the right time to the right users. Shout-out to my fellow Data Engineers.

It is crucial that data delivers value because data that is not tied to business value becomes a cost center that drains hundreds of thousands of dollars.

You don’t want to collect data and just analyze it. You want to transform it, extract value and push the value back to the customer, the shareholders, and the company itself.

Some data architecture foundations that help generate business value are:

Having a Single “Source of Truth”

If each team has access to different information, they are bound to disagree.

When business units look at their own slice of reality and set their own definition of value, there will be confusion around which data should drive a particular decision. These discrepancies cause teams to come to a poor decision or cause errors in the resulting deliverable.

Data silos also make data inaccessible to people outside the department or team.

You need to ensure data from external and internal sources is available uniformly throughout a company so all teams have access to the same information. This data acts as the single source of truth where the goal becomes business outcomes, not ownership.

Data Integration

The technologies/tools in the target data architecture you choose should integrate well to obtain a unified view.

This holistic view of data drives productivity.

Otherwise, lots of time gets wasted to unlock the value of data if there’s a vast amount of structured and unstructured data stored across different platforms.

Think integrating data across relational databases and NoSQL databases, data visualization tools being incompatible with the data warehouse or data catalog and data lake not liking each other.

Data Governance

You can only trust insights from good-quality data because the insights extracted from low-quality data are inaccurate.

It’s crucial to have a set of guidelines that help ensure superior data quality. This starts with the goal of enabling more access to data, not restricting it.

Data Accountability

You can implement security and privacy by design at every step by shifting from data ownership to data stewardship because it has a greater degree of accountability.

Data ownership defines who has the ultimate control, authority, and accountability over data within an organization.

Data stewardship ensures the quality, integrity, and appropriate use of data throughout its lifecycle.

Few ways stewardship can increase the quality of data:

• Stewards can “label” raw data to ensure consistency and quality
• They become responsible for educating colleagues on the data that falls under their stewardship
• They can validate and publish data used by others

Data Analytics/Machine Learning

Buying or building data analytics and machine learning/artificial intelligence to transform business results for your company would have greater impact after setting up everything we discussed.

Building a Company Culture of Data Literacy

Building a culture of data literacy is the quickest and most efficient way of building a data-driven company. Data literacy is the ability to read, write, and communicate data in context.

If you have the ability to describe the use cases in which you use data, applications, and the resulting value, then you have data literacy skills. This involves understanding data sources, their architecture, analytical methods, and applied techniques etc. on a high level at minimum.

These skills allow you to translate the data into compelling, visual stories that stick with stakeholders and senior leadership. Achieving concrete business results becomes easier as you transform data into actionable knowledge.

Almost every role in today’s world uses data. Therefore, companies need more people with the ability to ask the right questions about the data, interpret raw data, and draw insights into a clear story or action plan.

When most of your colleagues in the company can make better, data-driven decisions that lead to better results, there is a culture of data literacy.

These are the foundations for an excellent data culture:

Democratize Data Across the Company

Allow your colleagues to easily access, store and analyze data so it empowers them to act. This is a foundational step toward building a data-driven company.

Organize Data in a Transparent Manner

Communicate metadata for data sources to intended end users to add relevance to data. Metadata that’s immediately useful for every level of expertise includes

• Data origin
• Trustworthiness
• Quality checks
• Rules and compliance policies
• Business value of a data source

With metadata you allow everyone to understand the data, its lineage, and how it flows within an end-to-end process rather than just a single part of a process.

Train People to Use and Analyze Data Responsibly

Train people so they not only develop a good understanding of your company’s data tools but also use them to accomplish their goals.

Lead with empathy to create data leaders

Create space to allow people to challenge teams on data insights that raise questions. You can question the existing data and the processes around it enhances the data culture.

When you don’t always take data at face value, you ask:

• What data do you have or get which supports or contradicts this business case?
• Are the sources reliable?
• Is the analysis correct?
• What checks have been made?
• Are other sources of evidence consistent with this story?
• How important is the decision? What further evidence will I need to act?

Data Driven Decision Making

It is easy to recognize the value of data, collect lots of it, and masquerade as a data-driven company. However, if you look to harness the wealth of data that’s available, you unlock data as a true differentiator and help your company make evidence-based decisions.

With well informed decisions, your company understands its customers, optimizes operations, identifies emerging trends, and capitalizes on any untapped opportunities better.