How to Transform Data from Just Ones and Zeros
Data are king but for many companies they are more of an eminence grise.
Technologies are increasingly involved in the operation of companies. Therefore, it is not surprising that the volume of data that each company generates is also growing very quickly. The problem is that 80% of this amount just lies idle and companies do not actively use it (IBM).
But if we take a step back, not only are the data not used, companies don’t even structure them. TechRadar reports that 90% of data is in a state where it cannot even have informative value for the company because they are not properly processed.
This is a huge problem at the time of AI’s entry into companies. In order for AI to function effectively, it needs properly prepared data.
So what is the key to a company being able to make much more out of the data it has stored than just content that takes up computing resources? We will now look at a detailed analysis of this topic.
What is dark data?
This term was coined by Gartner and refers to data that are not actively used in corporate decision-making. Companies often create dark data from logs, call center records, emails, documents, old records, or data collected from IoT devices.
Such data just take up space and collect dust. But it is possible to turn them into sources of key information for predictive activities, optimization, even risk management and compliance.
Data are a sunk cost, although they could be a tool for higher revenues or cost optimization.
Why should you, as a B2B decision maker, be interested in this?
While we’re on the subject of data-driven decision making, let’s back up the answer to this question with real numbers.
As a decision maker, you have to make decisions, obviously. HBS reports PwC research that shows that managers who rely on data make several times better decisions.
The company McKinsey in its survey points to the higher profitability of companies that make decisions based on data compared to companies that do not use this approach. How much higher is their profitability? Nineteen times.
The objectivity of decision making is also higher. As humans, we tend to look at decisions about corporate activities subjectively. However, if a company is to make the best decisions, it needs to be based on objective data. The subjective ones often do not correspond to reality.
At the same time, the company also meets the expectations of customers who want a personalized experience when interacting with the company. This “personal” approach then increases ROI. By how much? That is a matter for the specific company. However, we can say that the return on investment is maximized when data is used to its fullest.
How to make data a key member of the team?
To make this change happen, a company needs to choose an approach to its data that will lead to effective work.
There are many different frameworks, but the key step for all of them is attitude. If you are not guided by data in your company’s decision-making, but rather by intuition or feelings, it is useless to spend effort and money on processing data for strategic decisions.
However, if you want to make decisions about the company based on real data from your operation, then it is crucial to approach the operation purely analytically, even scientifically.
For the company, this means that it will appropriately process the data into the right formats. It will use hypotheses, tests and in-depth analysis of the results. The pillar is finding answers based on data, not supporting opinions with data and fitting them to the desired state.
Which departments will benefit from the data?
We are still talking about the benefits for the company as a whole but it is also good to break down the entire operation into individual departments and see the specific benefits in a more detailed context of specialized activities – marketing, sales, and operations.
Marketing
This area is quite logical. In order for a company to be able to best target relevant potential customers, it needs to know where to find them and what is valid for them. In order for a company to be able to satisfy human tendency to have personalized offers from any field, it needs to know how to achieve this.
In addition, data help to evaluate the effectiveness of individual activities and it is possible to optimize costs where it makes sense. Feedback, in turn, helps to perceive whether there is a need to adjust some area of operation to increase the satisfaction of existing customers.
Sales
This department is closely related to marketing, but there is one area that needs to be mentioned separately: intent data.
Nowadays, there are business tools that can gather information about potential customers who are ready to buy a specific product or service. Although we have limited options in the Czech Republic, there are also paid tools that make this data available to us.
They are especially valuable for B2B sectors, where the life cycle is long and the readiness of the potential customer is very important. You can find out more details about this principle in this short video.
Operations
This term encompasses a truly wide range of activities, but the use of data for decision-making is best seen in areas where IoT sensors can be deployed.
Here are three use cases from our customers.
- A mining company installed special sensors on its industrial screens to be able to predict technical faults on these devices and thus minimize downtime of individual machines.
- A retailer installed sensors in its stores to make more efficient use of costs for air conditioning.
- A food manufacturer checks the storage conditions of products to prevent deterioration and prevent the consequences of power outages.
Regardless of the field, the Internet of Things can help with cost optimization. But only if 3 conditions are met: data collection, analysis and visualization, and output management.
So how do you do it?
We’ve already mentioned the first step – attitude. So once you’re ready to operate on the data-first principle in your company, what can you do to make the most of it?
- First, you need to translate your company strategy into numbers. What do you actually want to achieve and which data will help you do that? The goal is not to turn all data into information, only the data that is relevant to you.
- Then you need tools that won’t create data silos, but will help you gain a holistic view of critical areas. This also includes the possibility for employees to work with this data so that their work is based on a data-first approach.
- Then it is important to choose the right visualization. Depending on the target activity for which the data is to be used, it is necessary to choose the display methods. If we take the specific examples that we have already discussed, for some people it is only necessary to see the development of data over time, while for others it is necessary to carry out follow-up activities that help with predictive analysis.
- An important part is also training employees so that they know how to apply the company’s approach to data in their daily working life. Even the best processed data and first-class tools will be just wasted money if the team does not learn to handle them correctly.
What to watch out for?
One area is certainly data silos which we have already mentioned. Another stumbling block is often poor data quality. It is not just about collecting data and uploading it to some software. Data must have the right formats and metadata, especially when we need to use them for advanced tasks.
It is like food. If you eat spoiled food, you will get sick. If you base a decision on poorly processed data, it will turn out badly.
At the same time, it is also necessary to keep all decision-making activities in line with legal obligations. GDPR is not the only regulation that affects data processing. And there will only be more and more of them.
A leap of thought, since we are talking about GDPR. If you do not have an overview in your company of which data you collect and what you do with them, then you can be in big trouble as soon as someone asks you to exercise their rights and delete information about them.
What now?
Data collection should not be the end of the road. On the contrary, for a company to be able to use data successfully, it must be seen as a valuable tool. So don’t collect data just for the sake of collecting data. Find the data that will provide you with invaluable information to improve the operation of your company.
