Building a More Data-Driven Culture

At some point, every company asks themselves the question, “Am I succeeding as well as my competition?” In a competitive landscape, no one operates in a vacuum.  If you are not operating at the same level as your competition, then you are looking for ways to improve in order to gain a competitive edge or advantage. It quickly becomes a game of process improvement, which can occur in many forms such as brand awareness or supply chain and logistical enhancement. Yet, at the crossroads of all process improvement questions lies data. Data is fast-becoming the new disruptive force in our changing world. The company that, not only has access to the right data, but knows how to utilize it correctly, can be the one that rises above the competition.

Perhaps this seems obvious to some; however, many executives still fail to realize the power of data analytics. Companies that try to transition to a data-driven culture face enormous internal resistance. In fact, according to the New Advantage 2017 Big Data Executive Survey, 85% of the executive-level respondents confirmed that they were trying to adapt their organization into a more data-driven culture. However, only 37% of those respondents believed that effort actually flourished. In in an ever-increasing, data-driven society, companies need their data-focused strategies to flourish, if they are to develop or maintain their competitive advantage.

So, how does an organization grow and nourish a data-driven culture? These simple, five-steps can help organizations achieve their goal.

1. Avoid Faulty Assertions and Personal Bias When Driving Decision Making

Data analytics is not about “What your gut is telling you” or “What you believe.” It is about  undisputed, provable fact inherit within the data. Often, executives lead with similar statements that are based on assumptions and theories, rather than fact. Can an executive have a gut feeling that is confirmed by data? Absolutely, but leading by gut feeling translate to leading by assumptions based on incomplete information or pre-conceived notions. If you want to make better decisions, then you need high-quality data and stronger data analysis. This means setting aside personal bias and utilizing the resources that you have to guide your decision making through an evidence-based thought process

2. Treat Data as a Resource, Rather than Just a Tool

When data is used frequently, it can easily be treated as a tool. The problem with the tool-based mentality it that it does not associate value with the data. By establishing the value of data early in the analysis process, a framework of priority is established for cleaning the data, updating datasets through collection, assuring quality control, closing potential gaps, and defining key performance indicators. Emphasizing the value of data can lead to sounder, more solid, decision making.

3. Don’t Overcomplicate It

Overcomplicating the data analysis process can lead an organization to feeling intimidated and overwhelmed. People will resist data analysis implementation if they feel overwhelmed by the tasks and deliverables. Organizing data in a simple, well-structured location is an important step that can minimize frustration and angst during the analysis process. Centralizing the data allows teams to integrate data sets, provides greater accessibility and increases usability. A complicated system can discourage team participation and create frustration, but a clean and simple system can support and even encourage team participation by providing value to the team.

4. Incorporate Meaning Beyond the Numbers

It is not enough for organizations to know their numbers. They need to know what those numbers mean for the future of the organization. Data analysis must be actionable. Set tangible goals or establish a clear mission that aligns with data reporting efforts. The key performance indicators (KPI) must be applicable and relevant to the organization’s strategy. Simply phrased, data informs decision-making. If the data collected and reported does not enhance decision-making, then it is a wasted effort that can be costly and ineffective.

5. Turn that Data into Action

Being informed is not enough, and having actionable-data is not enough. The organization must act upon the information! In order to foster a data-driven culture, the organization must leverage the information by taking action. Only then, will the data collection, analysis, and reporting efforts have value. Too often organizations are held back by inaction. They never leave the well-informed, theoretical phase of chasing the next big thing. Data might inform decision-making, but it can not force a decision or action. That is the responsibility of the leadership team.

The world is constantly changing, and the business environment is always evolving. Organizations must adapt to the change if they want to build or maintain a competitive advantage. This means reaching beyond an understanding of the importance of data and learning to leverage data for strong decision-making. Only then, can an organization chart an evidence-based strategy that yields results.

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