In an ever-increasing competitive landscape, being data-driven is often overlooked as being a primary means of differentiating yourself from competitors. What does it mean, however, to truly be data-driven, and more importantly, how can you get your organization to a point where they can truly wear the “Data-Driven” badge?

What does it mean to be Data-Driven?

“Driven Organization” Defined

Many organizations understand the benefits of using analytics to drive the business forward and want to take action. One of the key drivers that stakeholders are seeking is cross-departmental synchronization, which enables open communication of goals across all departments to drive business decisions. The largest commonality to aid cross-departmental synchronization is data and insights.

Being truly data-driven lies in the determination of where data and analytics capabilities rank on importance in business strategy, business priorities, and business decisions. Historically, at 3Cloud we’ve found that organizations seek change because:

  1. Something has gone wrong
  2.  They’ve heard great things about how competitors are using data-driven insights to drive their organizations forward and want in on the action.

This typically translates to organizations getting buy-in from their stakeholders to buckle down on their initiatives and start correctly using data as a tool to enable better business decisions, in all facets of the organization.

Business Benefits of Being Data-Driven

In order to understand the benefits sought, an organization first needs to figure out its priorities. The prioritization of analytics typically comes down to determining where it ranks in order of other organizational priorities. For example, are you looking to optimize your supply chain, reevaluate your vendors, change your product line, or target customer retention? Lexy describes how each problem and priority relies on or should be reliant on analytics, to drive the end result to the optimal point.

“What it comes down to is, evaluating not only that you have a number of priorities in your organization, but that analytics can support all of those priorities, making it a part of those priorities.”

Ultimately, the benefits are innumerable.

Common Challenges to Being Data-Driven

This interview details that the level of difficulty of becoming a data-driven organization is dependent on a plethora of factors. There are instances of smooth transitions as some organizations have great communication cross-departmentally. However, in instances where leadership isn’t as communicative and doesn’t understand the value proposition, or the “What’s in it for me”, to their employees, initiatives can fall short. Resistance in these examples often comes in the form of disregard. If leadership does not present to each department why being data-driven is important and valuable for them, they will often ignore the new capabilities and continue with how they’ve historically done their jobs. This is incredibly common in organizations where the company is performing well. In these situations, it’s important to emphasize that although performance is great now, having preventative measures to ensure it will be in the future should be just as high of a priority.

Data-Driven in Action

Brick and Mortar Versus Online, Which Wins?

In this video interview, Lexy Kassan details an experience with an organization that previously relied on gut feel to drive business decisions. This retailer engaged 3Cloud to identify the overall impact of store placement in new locations. This was driven by the fact that the retailer was experiencing less growth in new markets than expected based on in-store sales, and they wanted to uncover insights as to why that may be. The 3Cloud team discovered that when this retailer went into a new market there was about a 33% lift in their online sales.

This insight allowed them to conclude that they were still gaining business from entering new markets, just not in the same way they expected. The success of this engagement, originally for the finance department to evaluate their investments in specific markets, drew interest from other departments within the organization such as merchandising, planning, and product design. At the year mark of the engagement, the retailer began showing more broad interest in truly adopting analytics as part of their processes.

Changing Mindset: Steps in the Transition Process

How do companies become Data-Driven

The most important factor in an organization’s ability to be data-driven is whether there is executive buy-in or not. For a shift in a company’s perspective to not only occur but stick, the push needs to come from the top. Senior Management needs to lead the charge and be empowering those below them to use data in their decision-making processes. For this to happen there is a significant amount of preparation that must be done. This could include technical integrations, operational changes, change resistance planning, and learning tools and technologies, to list a few.

How can organizations use Organizational Change Management to Be Data-Driven?

Organizational Change Management’s (OCM) sole focus is to help organizations with transitions. These processes are put in place to help explain and provide clarity cross-departmentally on not only why the change is occurring, but why it is valuable, and how it will help the organization to be more successful. OCM allows for employees to have insight into how their roles will be affected and how it will make them more effective. This is important because combating change resistance is as simple as allowing an employee to truly realize the value of the change and how it will help them progress in their own careers. This is done by the implementation of new processes. When organizations shift from gut-feel decision making to data-driven decision making, having processes in place to break down how departments and individuals will utilize data is arguably one of the most important components.

Operationalizing Analytics

When it comes to the implementation of data and analytics, operationalizing your analytics is one of the most important components in your organization’s success or lack thereof. What good are the data and the insights, if it’s all being interpreted in different ways? The biggest benefits are only gained when you use those learnings and machine learnings as part of dashboards that employees are seeing or getting their hands on daily.

Truly operationalizing your analytics can be defined as using the insights gathered from the models and data science tools, getting them into the hands of users, and training them to make informed business decisions based on them. It all comes back to empowering your organizations’ employees to make those decisions, leveraging the data, and really giving people the tools to see data and use it.

Overcoming Data Fatigue

Data Science in the Mix

According to Gartner, “83% of all big data models that are developed never actually make it into production.” This often results in organizations feeling like they’ve tried and failed at becoming data-driven, otherwise known as experiencing “data fatigue.” These projects, however, are often isolated. Any particular model can have a plethora of different use cases. This is why it’s important that as many stakeholders as possible are involved in the process of implementing these new initiatives. Why? Because if Data Science projects and models are communicated well throughout the company, the end results may not be accepted or useful for the entire organization, or on the flip side, could take longer than expected and require a larger lift, more resources, or different capabilities.

How long does it take to become Driven?

Becoming completely and truly data-driven ranges in time-frames and can take years. Typically this is a result of organizations needing to build up analytic competencies across the board, develop integrations that they may need, develop expertise, and influence and change the culture of the company and the way people think about the business. There is often a significant amount of data governance and data quality implementation that will play a role in the time frame as well. Unfortunately, it does not happen overnight, if it is done correctly. This is because being truly data-driven needs to incorporate a multi-faceted strategy that will overcome all your organization’s challenges.

Wrapping it up

At 3Cloud we understand that becoming data-driven can seem overwhelming and that implementation can be riddled with obstacles. We, however, have the experience, expertise, and framework in place to guide your organization to success can alleviate the problems that you’ve faced in the past. If you’re interested in learning more about incorporating data and analytics into your organization, contact us here.