OMNIA Partners Blog

How to Make Your Company Culture More Data-Driven

Posted by Kloeckner Metals on May 09, 2017

OMNIA Partners, has invited industry experts to share insights on achieving manufacturing and business success. In this post, Jonathan Toler, of Kloeckner Metals discusses how companies can make more strategic decisions through better use of their data.

data-driven-company-cultureData Isn’t All or Nothing

Digital transformation is the buzzword of businesses everywhere who are rapidly trying to digitize their organizations to stay competitive. Digital transformation starts with data and building a culture in your organization that’s data driven. But, for all the hype, taking those first steps towards becoming more data driven doesn’t have to be a painstaking, all-in organizational restart. It can start with incremental moves that make data more accessible, bridge siloed departments, and, finally, tie data with departmental and organizational outcomes.

What Isn’t Data Driven

Data is abundant and, unless you’re buying servers to host it, data is cheap. With so many more individuals living their day-to-day lives online, the amount of data worth analyzing is expected to double by 2020 according to IDC. But, having access to department data and pulling reports ad-hoc is not the same as being data driven. Even dashboards, long seen as the crown of analytics, aren’t enough.

Michael Dell, the founder of and CEO of Dell Technologies, put it well when he said, “If you look at companies today, most of them are not very good at using the data they have to make better decisions in real time.” That’s because unless data is integrated into business operations and the delivery of business services to customers, all that data is effectively what industry analysts call a “data swamp.” They’re pulling reports, they’re using dashboards, but they aren’t tying the data to business services in an actionable way. That’s not data driven.

What is Being Data Driven

The difference between not being data driven and being data driven is the difference between “big data” and “actionable data”. The IDC predicts that by 2020, the organizations that are able to separate out and analyze their most relevant data and deliver actionable information will gain an extra $430 billion in efficiencies over their less analytical competitors. That’s huge, and businesses are perking up. By 2016, 48% of companies had already invested in big data, and nearly 75% of those invested again in 2017, according to a study by Gartner.

It’s increasingly important that businesses, if they are to capture that value and stay competitive, become data driven. Big data is messy and unstructured, making it near impossible to derive meaning from it, but there are many steps businesses can take to start inching their company cultures towards data analysis and actionable insights today.

Democratization of Data

The first step towards a data-driven culture is democratizing data. Make the data departments need available to them. In fact, make data as freely available as your privacy considerations allow. The second step is to make sure that departments and employees have a clear understanding of not just their own KPIs and goals, but the KPIs and goals of other teams. Whether or not they have them, empower employees to create or break down their quarterly KPIs into smaller monthly or weekly chunks. Finally, make sure your departments are trained on the tools that are already available to them and consider lending some assistance when it comes to identifying those data points and metrics that are most relevant to their goals, whether it’s Tableau, Qlik Sense, or something else.

Data is being used to improve

Entrepreneurship thought leader Seth Godin said, “Organizations that do nothing but measure the numbers rarely create breakthroughs.” Once departments have identified both their goals and the data relevant to their goals, it’s time to get them in the habit of not just measuring data, but encouraging small, incremental improvements with A/B testing. A/B testing measures the performance of two digital assets that differ in one key area, allowing organizations to hone in on opportunities for growth. With digital tools that are inexpensive, easy to implement, and can identify opportunities for sizeable improvements, businesses are currently living in the golden age of A/B testing.

Big Tests

The maxim in growth testing is that the bigger the test, the bigger the result. Organizations taking their steps into being data driven will want to run bigger tests first since it’s likely many of their processes are based on untested assumptions or inherited practices. Big tests can involve everything from testing different value propositions via landing pages to testing new outreach approaches on sales leads to improving department efficiency. The beauty of any testing whatsoever is that it will force the hand of any department that’s debating what data is the most valuable.

Small Tests

Smaller tests are the most valuable when organizations have already tested the bigger variables and are looking to optimize. Small tests can run the gamut of changing button colors, tweaking copy, or modifying call scripts. While small tests are unlikely to uncover huge drivers of growth, the cumulative value of continuously running them can be substantial.

Digital Tools out there to help

There are a few important considerations to take while running tests. First, you should make sure that you can isolate the variables you’re testing by keeping every other variable constant. Otherwise, the data won’t be reliable. Second, you’ll need enough traffic or leads or funnels to get to some level of statistical significance. Many tools out there, like Optimizely, Mixpanel, and Google Analytics, are partially or entirely premised on the value of A/B testing and make it downright accessible.

Collection and Feedback Loops

There are many untapped sources of data that digitally transforming businesses must loop in because their impact on business services is unquestionable. While the eventual goal of digital transformation will require a holistic approach to data and analytics that spans the entire business, there are a few sources of data that organizations can bring on board as a first step.

Potential Data Sources

ERPS, CRMs, & Databases

ERPs, or enterprise resource planners, CRMs, or customer relationship managers, & databases are just a few of the enterprise systems that should form the foundation of data. Since 2010, companies have put a lot of money and effort into pulling data from these systems and into robust reporting applications. The good news is that traditional applications that historically were stored on business services with all the attendant hardware setup, maintenance, and backup costs are going the way of the dinosaur. Instead, SaaS-based apps that are stored on cloud-based servers are inexpensive, quick to update, and scale up, making ERPs, CRMs, and databases accessible to most all businesses.

Web Analytics

Between Google Analytics, Omniture, Mixpanel, and KissMetrics, there are a wide variety of web analytics sources out there to help you understand what is happening in your online world. But digital businesses must identify the target KPIs and stick to reporting that identifies growth towards them. Unless goals are set up in each and every reporting applications, businesses will still be stuck in a “data swamp.”

Customer Feedback

Customer feedback is vital. We at Kloeckner run a net promoter score (NPS) survey for our online products (our score is 65). This NPS score helps us look past the pure dollars and clicks and shows how customers feel about us and their loyalty to our digital products. Further, we’ve identified those factors that are positively associated with our NPS and are at work methodically improving them. This has been a huge opportunity for us to improve retention and the lifetime value of our customers while encouraging referrals and reducing sales costs. For example, companies in the home internet and TV industries generally have very low NPS scores due to persistent service issues while a company like Tesla has a very high NPS score (96) due its commitment to customer service and high product quality.

IOT & Sensor Data 

One of the hottest new trends in manufacturing is compiling sensor data into the rest of the data fold. For example, we at Kloeckner have started integrating RFID into our service centers. These sensors allow us to better understand the flow of materials, personnel, and machines in order to achieve greater efficiencies in maintenance and safety. While NPS is a top metric when it comes to marketing and sales, the data we’ve gathered from RFID will be a boon to our operations and logistics teams.


Alongside the things newly data driven businesses should be doing, among them identifying KPIs and goals, increasing the sources of data, and running frequent tests, there are certain risks organizations take on as they start to grapple with digital transformation. Here are a few to avoid.

Avoiding Analysis Paralysis

Decisions should be based on data, but that doesn’t mean that decisions can’t be made even when all the data isn’t available. By necessity, being an “actionable data” company means identifying those sources and only those sources of data that impact business delivery, but business leaders simply may not have all of that data all of the time. The key to avoiding analysis paralysis is to make a decision when the delivery of business services demands it and understand that the decision was made based on the data available then. It’s perfectly acceptable if data comes to surface later that would’ve impacted the first decision. Digital businesses can’t afford to wait. Rather, they move, and then readjust later.

Avoiding Silos

I once worked for a marketplace company that split its business into “buy-side” and “sell-side” businesses. Synergies were never created even though most of our customers were both buyers and sellers because the reporting analysts, product managers, and management teams never communicated and never shared their findings. Avoid silos whenever possible.

Avoid Closed Systems/Partners

Don’t choose technology or partners that don’t share data. While an API or XML file feed is the best, your partners and technology providers should always allow for YOUR data to be accessible to you. On the flip side, they should also be able to work with you and draw insights from your data even if it’s proprietary. No matter what, it’s important that your data is centralized and accessible by anybody and everybody at the organization who needs it. In general, try to pick as few tools as needed to get as much access to your data as possible. This will help minimize configuration and maintenance issues while enabling your team to move on your data right away.

Make The Decision to be More Data Driven

Becoming more data driven is no longer a choice; if businesses are to continue to capture growth, it’s a necessity. It’s time to move beyond using data to reflect business performance and to start utilizing it to drive business operations. Ultimately, it’s only a data-driven culture that will be able to bridge data with results and establish an organization that’s definitively growth oriented. Business leaders who make data and analytics part of their business strategy and who start the process outlined here of cultivating a data-driven company culture will find their potential for business growth is exponential rather than cumulative.

Topics: Analytics and Technology

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