7 Attributes Of a Highly Data-Driven Organization

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Darshan Shah

August 22, 2022

According to the Mckinsey Global Institute, data-driven businesses have a 23 times greater probability of acquiring customers, a six times higher likelihood of retaining those customers, and a 19 times higher chance of being profitable.

"Data-driven" – recent times have seen a rise in the use of this phrase, and with good reason.

You can transform your company to be data-driven and experience more sales, better customer service, best-in-class operational efficiency, and increased profitability by embracing the power of digital insights.

What Does It Mean to Be a Data-Driven Company?

"The biggest challenge for many executives is that they base their understanding of the customer experience on gut instinct instead of research. Many executives say, "I would like X to happen for our customer experience because I know I would like that." The assumption is that the executive knows exactly what the customer wants, but that's not always the case. Instead, they should research to allow their customers to speak for themselves. So, listen to the data, not your gut," says Jamie Turner, Keynote Speaker, as per the Clootrack 102-Experts Report.

There is no one way for businesses to become data-driven; some may focus on building the right data team, while others may invest in the right technology or incorporate analytics into their digital transformation plans. When a business has a "data-driven" strategy, it bases its strategic decisions on the study and interpretation of data.

Simply defined, a data-driven organization appreciates the value of gathering raw data and the limitations of relying on empirical data to make decisions. Being data-driven, though, means going deeper into the data that has been collected, improving it, and figuring out how to use the knowledge that has been gleaned from the data to spur profitability and expansion.

It entails using the appropriate data whenever it is required. This can be done in various ways, including tracking consumer behavior, examining demographic information, collecting survey data, and more.

How Can You Build a Data-Driven Culture?

The adoption of a data culture is frequently hampered by a lack of leadership, which manifests itself as resistance to change, complacency, a refusal to employ technology developed by others, and fear of failure.

Here are 7 actions and attributes to help you build a data-driven culture in your organization:

1. Incorporate New Technologies

"One of the key challenges businesses face when trying to understand the customer experience is lack of data. Data is a key component of CX and helps us truly understand the experience. Many businesses focus solely on customer feedback or reviews as a way to ensure they are performing to the customer's needs. However, tracking journey time, drop-out points, and touchpoints show a more in-depth picture. Technology can play a big part in supporting businesses to track the experience. However, ensuring the team using it can analyze it correctly and really decipher what it means is crucial," says Lauren Harding, Head Of Customer Experience, Spring - in the Clootrack report.

Although adopting the correct technology is not a speedy approach to creating a data culture, technology and culture are interrelated since both rely on being receptive to novel ideas.

Answer these questions:

Does your company still use reports and dashboards?
Do you have on-premises enterprise data warehouses?
Are your data marts siloed?
Is your email the primary source of communication?

If yes, your company might have outdated technology and, consequently, a culture where data is hoarded.

Instead, you ought to invest directly into a portfolio of advanced technologies:

AI-driven insights
data lakes
collaboration tools
cloud-based, logical data warehouses
augmented analytics

These technologies can assist your business in producing automatic suggestions from sizable data sets and quality assurance assessments. This frequently pertains to a culture of innovation where:

data is democratized;
there is openness, clarity, and trust;
knowledge and insights are shared;
and people feel empowered and motivated to embrace the new.

This can assist your IT personnel in creating better end-user products and resolving problems with their present information architecture, paving the way for your company to become a data-driven business internally.

2. Source Data Right

Power stems from knowledge. Thus, businesses need to be aware of their own data and where it can be located to boost their influence.

The traditional internal and external data sources are already well-known to the majority of businesses. In addition to the present prominent data sources, there are more intricate ones. It is crucial to remember that every type of data necessitates a particular infrastructure for sourcing and handling.

Traditional Data Sources

Traditional internal sources are simple to find and easily accessible within a company's systems, such as:

resource management
billing
CRM

So, every business that begins a data-driven transformation should do a complete internal data revision.

Traditional external sources include external data that doesn't need sophisticated data processing and management infrastructure. This kind of information is typically gathered from:

statistics agencies
market research studies
official announcements
readily accessible public sources

Advanced Data Sources

Using sophisticated internal sources like web and mobile application logs, you can map a customer's journey through digital channels. Companies can better understand customer behavior with the use of this detailed information. Identifying the consumer behaviors that result in upselling, cross-selling, or retention is a huge advantage for the formulation of business strategies.

The only restrictions on advanced external sources are those imposed by imagination and a lack of technological capacity. Using publicly available data from social media and online forums, you can see how a company may evaluate customer sentiment almost precisely.

3. Accessible and Usable Data

Finding the data is a challenge, in particular for businesses with silos. Furthermore, canned reports delivered from informational silos are inadequate. Due to how the data relates to the function that their department plays within the organization, several team members may view the same data differently.

Making data usable and accessible is one angle to consider when examining the relationship between employees and data. So, firms should:

Reduce silos to avoid data duplication and coordination issues.
Ensure that the focus on accessibility is given to data professionals.
Verify that access is occurring at the appropriate discretionary level, following the laws and guiding principles.
Make sure you can utilize the data to the fullest extent possible.
Create procedures and systems that use easily available data throughout your company.

Departments and leaders can make crucial decisions without waiting for you because of complete data access. This open strategy promotes cooperation and increased accountability while discouraging unhealthy competition.

It will influence smarter IT, human resources, sales & marketing, and finance choices. Additionally, you'll maximize each team member's unique qualities in a way that exceeds their own skills.

4. Culture Transformation

It is crucial to concentrate on various viewpoints to supplement the wealth of knowledge. Therefore, businesses should adopt the following strategies to change their culture:

Establish meetings with a clear agenda and a set of facts to aid in making an informed decision rather than discussions that lead to irrational decisions.
Hire a chief digital officer or change agents who thrive on achievement before moving on to the next challenge.
Businesses should examine their attitude to innovation and ensure that employees are not blamed for attempting new things.
Accept hackathons, ask groups to work on challenging problems, and even praise failures.
Change your focus from what is already accessible to what the firm needs to solve with data.
Reorganize a collaborative approach around data and analytics.

This can entail bringing together business professionals, programmers, and technical staff. There is no ideal organizational structure, but the most profitable companies have data and analytics integrated into each business unit with some degree of centralization.

5. Continuous Improvement

An organization needs to have a data appetite to become data-driven. Your firm will accomplish its desired goals more quickly and accurately if you support a continuous improvement approach in your analytics pipeline. For this reason, your firm must:

Promote a test-and-learn methodology that allows for experimentation
Learn from errors to keep discovering new methods of applying data and producing new business insights faster.
Open up resources to access larger data sources that can offer your company insights.
Target many platforms and channels for marketing information.
Track product iterations, improve testing procedures, and solicit customer input.

This will transform your organization into a data-driven one by enhancing your teams' capacity to deal with data at scale and react swiftly to business events.

6. Encash Skills

It is crucial to monitor culture development, whether in the organization's analytical capabilities or the leadership behaviors displayed, and to put it into practice at essential times.

Another aspect of this is giving them the resources they need to acquire these abilities and behaviors. This can appear in a variety of ways:

Bootcamps
Leadership development
Mentorship
Real-time feedback

Without trained and empowered personnel managing the processes, having all the building elements of a data-driven culture is difficult. If left unsupervised, the established systems will produce unsatisfactory outcomes based on inaccurate or subpar data.

7. Data Governance

Many businesses are typically reluctant to be transparent, hiding information behind their firewalls and restricting access to digital assets. Building corporate empires around the data, complete with archways, moats, and thick walls, is equivalent: Although it may seem safe, transferring the data around is quite difficult.

However, businesses that rely on data risk misusing and tampering with their data. In light of this, strong data governance should continue to be the primary factor for every firm. So, instead of locking down data, you can:

create a security culture that distinguishes between sensitive and non-sensitive information and specifies who can access what;
build a secure environment that allows self-service access to data while retaining the capacity for administrators to limit access to the appropriate users;
maintain compliance with data privacy laws and regulations;
have clear data policies to avoid common mistakes.

The Bottomline - What’s Your Plan of Action?

A business that wants to be data-driven must integrate data analytics technologies more quickly into everyday operations. Furthermore, every organization should comprehend data sources regardless of size or technical improvements. This is connected to ownership, duties, and security. Recognize team members that consistently display the proper behaviors and act as culture catalysts to benefit the entire organization.

Another important goal should be consistent governance. Realistically, any attempt to integrate big data into the business would call for building a culture that supports a data-driven mindset. In this process, solid leadership and thorough employee training are crucial.