Founder and Managing Principal of DBP Institute. I consult companies on how to transform technology and data into a valuable business asset.

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Data and Analytics (D&A) is considered the next frontier for innovation and productivity in business. A Mckinsey report says data-driven organizations provide EBITDA increases of up to 25%. According to Boston Consulting, the majority of the top 10 innovative companies in the world are data firms.

But achieving a sustainable competitive advantage from D&A is very challenging. Many D&A projects are not very successful. According to Gartner, only 20% of the Data and Analytic solutions deliver business outcomes.

While there are many reasons for the challenges, the most common reason is the lack of data culture. Gartner’s third CDO survey lists data culture as the number one challenge for realizing benefits from D&A. An HBR report states that many big companies still don’t have a data culture.

But what exactly is a data culture? Technically, data culture is the collective beliefs and behaviors of the people in the organization for leveraging data for improved business performance. But why does a strong data culture matter?

Fundamentally, a data-centric culture enables organizations to be more effective and efficient. According to Forrester, organizations that use data to derive insights for decision-making are almost three times more likely to achieve double-digit growth. A report from MIT found that a data-driven culture results in increased revenue, improved profitability and enhanced operating efficiencies. Research from IDC shows that organizations realize the full value of their data when they have a data culture.

So, how can an organization build a data culture? While there are many methods, below are four key enablers for enterprises to build a data culture.

1. Inculcate the service culture.

Service culture is an outlook that focuses on consistently creating value and trust with stakeholders. This is because to provide consistent service, there has to be a reliable frame of reference on the service levels, and this reliable frame of reference comes from data. Consider these three key strategies to build a service culture in the organization.

Data-driven culture should start at the top where the C-suite makes decisions on growth, cost and risks using data. This can be further bolstered by being receptive to new ideas based on facts or data.

Treat everyone who consumes the products or services in the company as a customer. At the same time, a customer doesn’t always have to be the one who pays for the product or services. A customer can also be an internal stakeholder who consumes your products and services.

Build data literacy. A good level of data literacy empowers the organization to ask the right questions, acquire pertinent data, derive insights, validate assumptions and make decisions, so as to serve the stakeholders objectively, ethically and efficiently.

2. Focus on continuous performance improvement.

A consistent service depends on quality data to measure and improve its performance. At the core, measurement creates visibility, and visibility drives performance. In other words, performance management relies on quality data. Below are three key techniques required to build a measurement-driven culture using data.

Build a KPI measurement framework that encompasses both leading and lagging metrics. Research says that the number of KPIs in the measurement framework should be 7 +/- 2.

Formulate the baseline performance. The baseline performance is the current performance level that will be compared against future performance levels to validate and verify performance improvement.

Find owners for KPIs. The performance brings change and successful change initiatives rest on accountability or ownership for addressing the gaps between the expected and actual performance.

3. Emphasize consensus culture over hierarchical culture.

A consensus-based culture relies on insights driven by data, unlike the hierarchical culture where the decision-making is based primarily on title, position and seniority. Below are three strategies to build a consensus-based culture.

Include the right subject matter experts (SME) in the decision-making process. Research by Bain Consulting found that the optimal number of SMEs to make a decision is 7.

Validate the decision to the objectives, question, KPIs, assumptions, ethics and payoff data by having the right feedback mechanisms. Also, ensure that the problem is framed correctly and the decision is arrived at with minimum bias.

Realize performance improvements by breaking down the objectives into smaller tasks and setting milestones based on targets, control limits and specification limits.

4. Leverage technology.

While technology alone might not be the driver or solution to realizing the data culture, it is a significant enabler. Successful business transformation programs have a strong correlation to technology due to the scale, speed and cost benefits technology offers. Below are three strategies to leverage technology to build the data culture.

Capture critical data elements such as products, customers, assets and more in the System of Record (SoR) for a single version of the truth.

Deploy predictive analytics solutions to be a proactive organization and better manage business resources and cash flow given that predictive analytics solutions have the highest impact on business results.

Managing access to data for the right users with appropriate role-based access controls (RBAC) so that the data is secure and the organization can speak the same language of data.

Overall, without a strong data culture, organizations will miss opportunities to use the data for improved business results. But once the above four key building blocks are in place, there will be a change in the mindset of the organization to value data and insights. This will further enable the successful deployment of D&A solutions based on the level of D&A maturity in the organization.


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