Data is the new hot currency of the technological economy, yet many organizations still haven’t fully realized the true potential of data. By incorporating a data-driven mindset into your entire workforce, you can greatly improve every area of your business from product or service development to marketing to sales to customer support and customer success.
From personalization to geo-targeting, the customers demand more out of business to provide them engaging and compelling experiences.
Now, just putting a few tools on auto-pilot and using data as a reporting tool is no longer a viable option to stay competitive. The CIOs need to understand the importance of building a data-driven decision-making culture.
Meanwhile, many companies believe they have a data-driven decision-making culture as they produce many reports, or have dashboards throughout their company.
Unfortunately, it’s not that simple.
A data-driven decision-making culture is when a company’s growth is measured using data rather than a gut feeling, intuition, personal experience or past examples. This is usually referred to as evidence-based decision making in the scientific world.
A data-driven decision-making culture is where accountability and transparency are nurtured around data, and team members are driven by the decisions through hypotheses testing where data results ultimately drive the decisions.
Having a lot of operational data is a great start, but to be a truly data-driven decision-making company requires the ability to create strategic insights into what is influencing your key performance indicators (KPIs).
Having a deep level of understanding for the metrics that influence those KPIs, and the capability to do analytical reporting, will help process all your data and build a data-driven team that predicts outcomes, predicts trends, and discover new insights.
A number of hurdles exist in the way of achieving a data-driven decision-making culture. For one, the data-driven goals don’t usually align with short-term strategies and executive decisions. More than that, without guided organizational change and experienced data scientists, much of your marketing team and IT staff will remain woefully ignorant to their customer’s needs.
According to Forrester Research, the companies who are able to master data-centric strategy to their growth will collectively generate global revenue upwards of $1.8 trillion.
And with more and more companies stepping their foot in the “big data” pool, the need to become data-driven has never been more critical.
Single source of truth
A single source of truth is a controlled, central and blessed source of data from which the entire company can draw. It is the master data. And when you don’t have such data and staff on your workforce can retrieve seemingly the same metrics from various systems, inevitably those systems will yield different numbers. Then the arguments ensue that you enter into a she-said-he-said scenario, each player drawing and defending their position with their version of the truth. Or some departments may unknowingly use poor-quality, stale or otherwise wrong data or metrics and then make bad decisions when they could have easily used a better source.
On the other hand, when you have a single source of truth, you provide the best value to the end-user: the analyst and the other decision-makers. They’ll invest less time hunting for data across the company and more time using it. Additionally, the data sources are highly likely to be documented, organized, and connected. So, by providing richer context about the interest entities, the users are better positioned to leverage data and find actionable insights.
From the side of the data administrator, a single source of truth is preferable, as well. It’s much easier to prevent, document name collisions across tables, and ensure that the underlying IDs are consistent across tables and also run quality data checks. And it’s also easier to offer flattened, easier-to-work-with views of the key relations and entities that, under the hood, might have come from different sources.
The following are specific advice on how to incorporate data-driven decision-making culture into your entire workforce.
The trend toward data-driven decision making
As data is becoming increasingly more important, companies are responding to this changing business environment by adding new senior roles like chief analytics officer or chief data officer to the highest level of their leadership teams.
Shopify has a senior leadership position as senior vice president of data and analytics which was being headed by David Lennie who previously was the director of data science and engineering at
Netflix and senior vice president of analytics at LearnVest. These three fast-growing companies are clear examples that having a senior leadership role in data is very important.
How to build a data-savvy workforce
For many companies that don’t have a central team or focal point where a data function exists, following are six key things you can do to easily build a data-driven decision-making team;
1. Start from the top with data-driven leadership
Begin with the obvious: The leaders must lead by example. Today’s best managers are sharing their insights with their teams and leveraging data to help tell their story.
When the data-driven leadership team is not present, decisions are usually based on the HiPPO (highest paid person’s opinion). This is completely the antithesis of a data-driven culture. And you can easily recognize them when they start talking about their XY number of years of experience and start telling how they used to do things at company ABC. While that experience is important, it must be added with current data to make good decisions.
Great leaders foster an environment for testing and hypothesis making. This kind of culture is the foundation for growth. The use of an experiment or a simple A/B test to share insights will start to drive the right behavior throughout the company.
Also, as a leader, remember to celebrate both success and failures. According to the Harvard Business Review, more than 80% to 90% of experiments fail. And these failed experiments should be treated as learning opportunities that will help shape future key hypothesis.
2. Hire data-driven team members
Empower and encourage your HR department to screen every candidate for any role in the company with a data-driven mindset lens.
Although, your final goal may be to have a complete data analytics team, start driving a culture adoption across your company with each new hire.
Example, if you are hiring a new marketing program manager, does the resume include performance metrics and real examples of how that person impacted your company from a big picture down to the program level? And if not, then pass.
3. Look within your existing ranks
Hiring for data science and data analytics roles is increasingly becoming harder. Since this role has become recognized but many companies, it has become a highly in-demand skill set with a shortage of talent.
Based on the Sloan Management Review, 40% of the companies that participated in the survey struggled to find and retain data analytics talent. The good news is that many of your other technical resources might be good candidates to get things moving.
Find out who on your marketing finance, and IT teams are data-obsessed. These teams usually harbor individuals who have advanced their careers and impact within the company using data.
Some teams already have data specialist. Someone on your IT team has created ways to pull, push, and aggregate data for various corporate reasons to answer common executive questions. Your finance team will have better insights and data on past results. Your marketing team should be data-driven when trying to figure out new ways to optimize, segment and target their marketing.
The chart in the above image shows how most marketing team’s data journey is shifting from data capture (CRM) and reporting (analytics and visualizations) to more action-oriented benefits, including personalization into marketing efforts, using artificial intelligence and machine learning for predictive outcomes based upon past trends.
So if you fail to hire them, then start to nurture the talent you have and help them discover new opportunities and capabilities to learn and build out their skill sets.
4. Use data everywhere and incorporate it into your company culture
A data-driven culture is usually easy to identify, especially in team meetings.
Example, at Klipfolio, many of their team meetings are centered around a dashboard specifically focused on the topic at hand. And whether it’s a monthly customer retention meeting, a weekly sales huddle, or a user experience on-boarding review led by the UX department, each discussion begins with a review of the data shared on a big TV screen in the room.
Each team member is encouraged to ask questions and drill down on what is being shown. People are expected to question the data- what it means, what we can retrieve from it, and what we are missing to complete the picture. These meetings are important as a forum to continually challenge ourselves on how we think, what we should collect, and what attribution vs. correlations can we make from the data.
You can easily realize how data-driven a culture is as there is no endpoint. Ideally, you should not have too many static dashboards. The top KPIs may change by a small amount from year to year, but everything else is constantly being refined, challenged, and rooted to help you better understand what exactly is changing.
5. Create your own data dictionary and tools strategy
The data tends to be centralized with very few individuals within an organization who are data experts.
However, transformational companies are those that enable data to be available to anyone across the entire company. As the data becomes more easily accessible, having a central spot to share those insights, a data dictionary to define the key metrics and an inventory of the tools available is the key to your data-driven decision-making cultural success.
The variety and number of tools available for companies to leverage is exploding, and the data is growing exponentially that those tools are creating.
Most of the small businesses now use a CRM solution, a website, an email platform, and digital ads. Back in 2011, the entire marketing segment had only 150 marketing tools, but today, there are around 5,000 marketing tools. That’s a huge increase; it grew by 3200% in the period of just six years. And it’s not just marketing- the marketplace for HR platforms and software is currently valued at $14 billion.
So, the challenge for today’s leading companies is how to strategically take advantage of all this data from all these amazing tools.
6. Remember that data is not everything
A data-driven decision-making culture can only take a company so far. Sometimes you see companies get so deep into analysis, reporting, and testing that they become paralyzed. Also, if you focus more on the wrong things, you might not notice the huge wave that is happening around you.
Making the right decision
Harvesting all of this data is more costly than its value if it’s not being efficiently used to make informed decisions. And the CIOs need to lead the charge in an encouraging top-down approach to build a data-centric decision-making culture by developing processes for decision-making that reflects data insights, and at the same time, empowering analytics centers to encompass data and provide automated insights from a wider range of channels. Data without decisions is like dumping your money in the ground.
Meanwhile, we’re all aware of the value of big data in the next frontier of tech and IT. But, we’re not sure if most companies are leveraging data to its full potential. Data is not just a merely tracking or reporting tool anymore, instead, it’s become the impetus for highest-level decision making that enables technical coordinators to automate tasks and boost efficiencies at their company.
Creating a data-driven culture takes time
Changing the culture of a company doesn’t happen overnight, so be patient, take the time you need, and start small.
Build on successes, encourage other members of your company to follow, and invest in few tools to help you along your way towards becoming a data-driven decision-making company. Many data-driven companies tend to use several tools as the data sources will be spread out within most companies.
Breaking down the data silos is usually a big barrier in changing the data-driven decision-making culture. So, help foster an environment where metrics are internally well-defined and communicated clearly to the departments on a regular basis. And ensure that there’s one person who owns the project and is the go-to resource internally.
Actually, it becomes addictive after you discover your first “aha” moment that produces new insights.
