Bye-bye gut feeling – Master data-driven management in 5 simple steps.

Table of Contents

The COVID-19 pandemic continues to keep us on our toes in its second year. Many employees are still permanently working from home, communicating via Zoom, MS Teams or Slack and working together on projects using digital tools. For managers in particular, the switch was a challenge to start with and has since become a tour de force. This is because it took place at a pace that was born out of necessity and would otherwise have been much slower. As a result, decision-making and working based on gut feeling is becoming more and more difficult. In the following, we’ll discuss a much better alternative to gut feeling, which also makes decisions more reliable at the same time.

The past year has highlighted a key point: Companies’ digital transformation has been catapulted forward by involuntary digital disruption. It’s no longer a vague vision of the future, but is determining which companies can survive in the market.

It seems as if the “new twenties” are set to become a golden age. But who for and in what context? If there’s one thing that will determine the future and success of a company in the twenty twenties, it’s data and how it’s used to make decisions.

Data said to be “the gold of the 21st century” with good reason. But why is that? When we look at tech giants like Google, Amazon or Facebook, we have to admit that the success stories of current and future companies are written from cleverly used data. But there’s a catch here: companies must also be able to use their data and make decisions based on insights from that data. The key word here is data-driven management.

All that glitters isn’t gold

If you look at the different companies and industries in Germany, you might notice the following: Many companies collect data, but they don’t know how to use it in practice. The immense potential of Big Data falls flat if the data is not analyzed. According to the 2012 “Digital Universe” study by IDC International Data Corporation, just 0.5% of all data collected is actually analyzed. The study also found that not all data has the potential to add value through when analyzed.

In 2017, the Economist claimed that oil would no longer be the most valuable resource in the world, rather that from now on, data would be the most sought-after commodity. From that moment on, data was compared to oil. However, a very crucial difference between the two was neglected. Unlike oil, data can be easily extracted and the supply is increasing exponentially. Unlike oil, data can be used multiple times and new insights can always be gained from it. People who view data as the new oil may be under the misconception that it’s enough just to collect data. But this is just the prerequisite for the real benefit that data brings: Insights for fact-based, data-driven decision-making.

As a leader, data and digitalization are everywhere, but how can you implement them internally in your company? How can you set up an entire company to be data-driven? How can everyone – from you as a manager to team members – work and make decisions in a data-driven and, consequently, evidence-based way?

Data in Business, these industries need data-driven management

* Adaption of

On the path to data-driven management, it’s necessary to combine and coordinate a wide range of efforts – more than most managers would like. Poor performance in any one of four interrelated areas – technology, data, processes and change management – can derail an otherwise well-planned data transformation. In the end, the really important aspects, developing and communicating a compelling vision, crafting a plan and continually tweaking it in the process, and fine-tuning the details, are always about people.

The harsh reality is that in many companies, most of the data available is not up to the required standards. If this transformation is to succeed, it requires:

  •  solid data quality and analysis as a bare minimum

  • an understanding of new types of unstructured data (e.g., a driver-supplied image of accident damage to a car)

  • capturing large amounts of data outside your own company

  • use and integration of owned data (vendor-specific data that is limited by legal restrictions)

  • ruling out enormous amounts of data that has never been used (and never will be used).

Data presents an interesting paradox: Most companies know that data is important, and they know that their own data is of poor quality. But they squander this hugely valuable resource by failing to establish the right roles and responsibilities, and instead blame their IT departments for the sluggish pace of their transformation. From the Internet of Things to blockchain and data lakes to artificial intelligence, the raw potential of emerging technologies is immense. And while many of them are becoming easier to use and becoming widespread as a result, understanding how a particular technology will contribute to the benefits of transformation is extremely complex. What should be clear is that appropriate experts are needed to adapt a technology to the specific needs of the business and integrate it with existing systems. Complicating matters further is the fact that most companies have an enormous technical deficit – in the form of embedded legacy technologies that are either difficult or impossible to upgrade to new standards. These problems can only be solved with professionals who have the technical skills and are able to work hand-in-hand with the company. Ultimately, transformation will only succeed with “people skills” among employees. Because data-driven work and decision-making don’t just depend on domain experts, but just as much on the skills and will of business leaders.

Detention: Managers need to catch up when it comes to using data

Data-driven decision-making has been proven to positively impact business results. By expanding your skills in data literacy, data analytics, artificial intelligence, and big data, you gain a tremendous opportunity to optimize your department, both internally for process optimization and for selecting the right customer segment for the next marketing campaign. However, collecting data alone is not enough for this. The skills required to process it, analyze it and turn it into recommendations for action are equally important to create real added value for your company. Using data professionally and acting on the insights generated has significant, positive effects on sales, operating costs, innovativeness, time-to-market for new products or solutions, and customer satisfaction and loyalty.

But these effects have so far fallen flat, because it’s not just ordinary employees who dither over data use – managers, in particular, are likely to be less enthusiastic about data-based decision-making. Many are confronted with a flood of data and don’t know what is really relevant and how to interpret it in order to derive added value from it. Making decisions based on gut instinct feels easy and right. The reason is simple: almost all managers (93 percent) feel intimidated by data. That’s according to Oracle NetSuite’s executive survey in its “Unlocking Growth” report. As a result, 67 percent of respondents do not make data-driven decisions.

The right technology is not the only thing that is important for a successful digital transformation. You need the right talent as well as convinced and competent data-based decision-makers in key positions who have a high affinity for data. The ability to convince a large number of employees and managers to take on new roles as data customers and data creators is just as important. Specifically, this means being able to understand, think critically about, and communicate the data they need today, as well as the data they will need after the transformation. It also means helping employees improve their own work processes and tasks so that they can collect data correctly and use it to make decisions.

Numbers, please! Data tipping the scales

Achieve ambitious goals, continuously optimize processes, keep an eye on employee performance, and hire new people at the same time. In the hypergrowth stage, managers must be able to coordinate numerous, important leadership tasks – and preferably at triple speed. Clear prioritization is essential, and that requires a reliable decision-making process.

Another barrier in this context is that managers often lack confidence in their own IT departments to drive major changes on their own. Therefore, for holistic transformations all departments must be involved, especially IT. Trust can and should be restored precisely for this reason by improving communication. Managers in this area need to understand the strategic realignment in order to make the right, technological decisions.

5 steps to becoming a data-driven manager

1 – Get the executive floor on board.

Transformation works best top-down. That’s why your first step is to get the executives on board to successfully implement digital transformation. It helps all employees of the company if they feel guided and supported by management and department heads to carry out the transformation as a whole. After all, the data transformation will affect every department, every employee, and will require each individual to learn new skills. Not only employees, but also management must first want to see and implement the concrete benefits. It must be clear that strong growth does not necessarily mean increased productivity, because the transformation means upskilling and reskilling employees and a new focus in recruiting. You should also take into account the fact that day-to-day business will suffer temporarily. For this, you need the backing of top management. Ideally, a company-wide understanding of growth and productivity should be created. As growth and data-driven decisions increase, so will productivity and profitability in the long run.

2 – Turn data into a cash cow

The ability to make sound strategic decisions is the critical fundamental requirement for a successful, modern business. But for this to succeed, you need reliable data that reveals potential and trends, as well as providing clues as to where unexpected stumbling blocks are lurking. Although the potential is well known, many companies still work with Excel and completely different tools depending on the department, which means that they store their data in data silos instead of a unified data warehouse. This mistake results in incomplete data sets that make strategic decisions slow, error-prone, or even impossible. Data-driven organizations must perform the balancing act of keeping their tools up to date without getting lost in them. After all, it can be costly and time-consuming to keep retraining your workforce. Additionally, there’s a risk that employees who don’t get used to new tools will continue to use the old tools. This leads to duplication and more stress. Streamlined processes and consistent workforce training are therefore important tools.

3 – Create role models and motivate

Transformations offer the risk of empty phrases in big speeches that completely miss the goal of motivating. If you want to win your team over for the transformation, start where employees see actual and realistic benefits for their work. The company culture plays a key role in the transformation. Transparency and comprehensibility of decisions are particularly important. This means that business decisions must be explainable based on data and should be communicated internally. It’s not uncommon for there to be multiple ways of addressing challenges. If these are made transparent, other perspectives from specialist departments, as well as objections, can be communicated and considered. This prevents underlying assumptions that may be untrue from being used as a basis for decision-making. This is especially true for process changes where the affected employees need to be involved. In this way, you prevent processes from being adopted or even automated that don’t work and must first be adapted and streamlined. Therefore, it makes sense to openly communicate the end goals right at the beginning, so that employees can be involved. This makes it easier for them to understand what the purpose of an action is and to intervene if it’s not fit for purpose. Break old habits of decision-making and make decisions based on factual information. Because when you make your decisions transparent, you run the risk of asking difficult and smart questions, but in doing so you gain valuable insights and increase employee trust in the transformation.

4 – Your team as the gas pedal for data-driven business.

What’s the first thing that comes to your mind when you hear the word innovation? A new product, a machine learning algorithm, a smart new technology? Yes, all of these can certainly be innovative, but none of them would be actionable without a team to develop and manage them. Technologies are constantly evolving and vast sums are constantly being paid to maintain them. Ironically, there is rarely investment to ensure that the workforce also develops and expands their skills, while they are the true drivers of innovation and business value. It’s not enough to hire new data experts if existing teams don’t know how to incorporate the insights of a data analysis into their decisions. Invest in new technologies. Invest in capable experts. But invest equally in the skills of your employees. Only when they are prepared for the transformation will they be able to drive it forward and meet the changes with curiosity and drive. There’s no need to apply a scattergun approach. Every career level and every department has its own knowledge requirements and needs investment there.

5 – Become a transformation coach

Any change needs to start with someone who believes in it and is willing to advocate for it. Especially in companies that are in growth mode, many goals are pursued simultaneously and rely on individuals to register needs and drive innovation. Innovation can start anywhere, with you, with your team and it often starts with curiosity and a desire to optimize. Everyone can become a transformation coach and create sustainable value for their team, their company, their customers and even for society, because everyone benefits from innovation.

Transformation starts with you. With StackFuel, you have a strong, reliable learning partner at your side to help you along the way. We’re happy to help you delve into the world of data, understand the topic from the ground up, and apply it to your work. No matter what department you’re in or career level you’re at, or where you want to go, with us you’ll learn to build your foundational data skills and get the basics for data-driven management, or you can qualify for roles as a data analyst or data scientist. Our in-service online courses are made up of instructional videos, expert interviews, text content and interactive assignments, as well as business scenarios to apply and consolidate what you’ve learned. Our mentoring team will guide you throughout the course to help you reach the level of data literacy you need in a digital workplace for success – today and in the future. Learn about our course portfolio and learning environment now.

Laura Redlich
Laura Redlich
As an authentic Berliner, Laura quickly joined the creative and start-up scene. After studying Media and Communications Management at Media Design University of Applied Sciences, Laura worked as the editor in charge of Finance, Tech, Data and AI at IQPC and interviewed well-known industry pioneers at conferences. At StackFuel, Laura is steadily adding to the Content Lab - our varied offering of free content, webinars, and publications.

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