Data-Driven

mindset-icon_data-driven

The ideal state organization plans and evaluates its business using appropriate tools to look at carefully curated data. Organizations that adopt the Data-Driven Mindset tell stories that answer business questions in ways that the organization can turn into action. At different levels, these narratives may take the form of strategic themes, journey maps, or user stories. Executing on these will provide data that allows the organization to evaluate the success of the actions, allowing the organization to refine actions and decisions.

Current technologies allow companies to collect large amounts of data about everything from supply chain and manufacturing to customers' preferences and actions.

Tools to collect, store, process and analyze information have rapidly emerged and matured to the point that they are available to even small organizations. The Ideal State Organization embraces a Data-Driven Mindset to intelligently make use of the data as well as tools to avoid being overwhelmed by information.

This organization spends time investigating what data will be appropriate to making business decisions and evaluating the outcome of those decisions, but does not spend resources “fishing” to make sense of unstructured data. The quality of the data is an important consideration in this mindset, as is applying the appropriate tools to answer the questions being asked.

The Data-Driven Mindset is used to tell stories that answer business questions in ways that the organization can turn into action. At different levels, these narratives may take the form of strategic themes, journey maps, or user stories. Executing on these will provide data that allows the organization to evaluate the success of the actions, allowing the organization to refine actions and decisions.

While data gives security to an organization, it also provides insight into critical business decisions that impact the customer experience. An organization with a Data-Driven Mindset understands that acting on business goals or processes alone will not be successful. Instead, a Data-Driven Mindset leads them to use information to make the workflow of employees and customers better and more efficient, leading to measurable increases in revenue.1 When the data is mined, predictive behaviors can be cultivated and acted upon.

Rather than using data to reflect the outcomes and desires of the organization’s goals, an organization with a Data-Driven Mindset becomes skeptical of its point-in-time data, and strategically structures data flow to be continuous and from multiple channels to ensure a more holistic view. It uses data to inform business decisions rather than a destination the company is heading towards.

Characteristics

Organizations that have adopted the Data-Driven Mindset have four specific characteristics:

Personalization

Companies with a Data-Driven Mindset understand that leveraging the information they know about a person can help them make predictive choices to create a more personalized experience. Whether customer or employee, the organization creates products and processes in context and relevant to the people involved. The data allows for the organization to better understand the needs and motivations of the customer and uses the information to personalize offerings. The personalization also creates new opportunities for the organization to better connect with its customers.

Value-Focused

An organization with a Data-Driven Mindset utilizes data to improve workflows and processes, and to create relevant solutions and useful tools for the people involved. Researchers at MIT found that “firms that adopt Data-Driven decision making have output and productivity that is 5-6% higher than what would be expected given other investments and information technology usage.”2 By understanding the past and current state of the interactions based on data, the organization makes choices that brings significant value to the business and in turn creates ROI and loyalty.

Data-Driven Meritocracy

A Data-Driven Mindset allows everyone in an organization to evaluate decisions and activities objectively, reducing subjective and political influences. According to The Economist Intelligent Unit, “Organisations that rely on data to substantiate business decisions display superior performance.”3

Predictive Behaviors

Organizations that are Data-Driven are able to understand how their customers are interacting with and using their products. That knowledge allows them to better optimize those products and services. Aberdeen reports Data-Driven organizations experience a 27% year-over-year increase in revenue, compared to 7% for other organizations.4

Pain Points

Subjective Decisions

Companies that don’t adopt a Data-Driven Mindset find themselves fighting between silos and the political influence of senior leadership. Often it is the most senior individual’s opinion in a meeting that matters, due to the subjective opinions of people. In these organizations, there is value placed on these opinions over objective data when making critical decisions.

Too Much Data

Organizations that are not strategic and purposeful about their data collection process find themselves overwhelmed with the sheer amount of data. Data is collected in hopes of a future use but is not compared against anything to measure, comprehend or organize it so that it can actually be useful. These organizations keep data around simply for the hope of it bringing them a new competitive advantage or line of business in the future. These organizations are then burdened by data but not able to use it efficiently.

Data is Directionless

Companies are collecting data but not using it to understand behaviors, and the data is collected without a plan for meaningful analysis or action. These organizations find themselves with measurements and analytics but are measuring a point in time, though the actual scenario of what is going on is not accurately reflected. Whether it is because of siloed departments, immature goal-driven optimization, or poor tools, an organization that has not adopted this mindset will suffer being able to purposely improve their business. In these organizations, data strategy and analysis is rarely considered during the planning phase of product planning.

Conclusion

An organization in its ideal state no longer has to guess at the behavior of its users. Investments are made in how to collect, analyze, and act on this data in a way that clearly sets them apart from their competitors. With superior product development due to a deeper understanding of users, organizations that embrace this mindset see the initial investment in data not as a sunken cost but rather as an enabler for future growth.

References

  • ”Best Of Both Worlds: Customer Experience For More Revenues And Lower Costs”. McKinsey on Marketing & Sales. N.p., 2016. Web.
  • Moustakerski, Peter. “The Virtuous Circle of Data”. The Economist. N.p., 2014. Web.
  • Brynjolfsson, Erik, Lorin M. Hitt, and Heekyung Hellen Kim. “Strength In Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance?”. SSRN Electronic Journal n. pag. Web.
  • Lock, Michael. “The Executive’s Guide to Effective Analytics”. Aberdeen Group. N.p., 2013. Web.

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