Duned

How build a data-driven company

We all know that changing is often difficult especially when it comes to complex transformations such as the one that embraces digital. One of the biggest obstacles is not knowing where to start, which derives from an often absent corporate culture oriented to the use of data. A survey conducted over the past year among data analytics leaders around the world found that 61% of respondents believe that corporate culture, not technology or people, is the biggest impediment when it comes to become a data-driven company.

A research from the MIT Sloan School of Management gives us some insights on the way to go. The ability to use such data and to be disruptive towards the status quo, together with the right technology, are the starting points to break down that obsolete mentality and build a data-driven company. But let’s see in more detail what it means.

 

Divert your investments into creating a Data Lake

 

Data-driven businesses create more efficiency and they are able to improve customer service. They are also more efficient in terms of operations and they have more profitability. That’s what data say. This is possible, however, if in support of the activities there is a Data Lake from which we can extract information and insights and these must then be made “actionable”, or rather transform those precious insights from raw data into concrete actions.

But how? It is clear that smart investments are needed, based on the priorities of each company – let’s not forget that organizations are not all the same. Those who have obsolete technology will have to invest in new technological tools and cutting-edge data analysis tools. This is often related to an innovative culture in which data is democratized – this means that it is available for all company branches -, there is transparency and trust, skills and insights are shared and people feel empowered, and indeed encouraged, to embrace what is “new”.

How to translate data into quick decisions?

There is no single path when it comes to become a data-driven company – some organizations focus on building a dream team of data scientists, others invest in the right technologies, and still others integrate analytics into their digital transformation strategy. For example: compared to traditional companies, which may have deep-rooted processes and leadership reluctant to innovation, startups have an advantage precisely because of their ability to immediately integrate data within their structure.

The lowest common denominator of all data-driven companies is – it should be – the speed with which decisions are made. But to do this, it is essential to integrate data from all the touch points that an organization owns with its Data Lake. It is possible to create customer engagement paths that can increase loyalty, conversion and sales by mapping and activating all available physical and / or digital touch points, and developing traffic generation and traceability systems for all consumer activities. This is possible if we make quick decisions that lead to competitive advantages.

 

Can AI be an ally in order to stimulate change?

Building a data culture is also difficult because it requires transversal skills. A solution, if you want to revolutionize the status quo, could be to look for someone who has the task of stimulating change. Which can also mean hiring a chief digital officer, who is often even known as a “serial innovator”.

What is his role? Encourage innovation. This doesn’t just mean adopting Artificial Intelligence and Machine Learning tools, but also making sure employees aren’t penalized for trying new things. In order to stimulate that corporate culture we talked about, successful companies periodically organize hackathons, they challenge teams and they make them tackle tough problems, and even celebrate failures. Because that’s how and where we start to improve.

Of course, investments in Artificial Intelligence can’t be ignored, because it is able to analyze, cluster and interpret customer data, transforming them into sources of knowledge and insights; thanks to image recognition algorithms it is possible to create and correct product positioning strategies and competition analysis by simulating real cases and obtaining new data from where you can build predictive models; but this is also essential when it comes to create clusters of customers in real time in order to involve them in complex campaigns that contact them with personalized messages or to enhance and streamline the management of customer service touch points.

 

How well do you know your customers?

We have already said that data can be used by companies in order to derive important information about their consumers. But it’s crucial to understand what exactly you want to get out of that data. In other words, we need to shift the focus from “what data do I need” to “what problems can I solve using data?”. It is therefore important to know the final consumer very well, his habits, his preferences, and then reach him with personalized campaigns and messages. The customer must not feel “one among many” but must always have the impression of playing a special role, let’s say privileged, in the relationship with the company. In this way they will become loyal customers and, even more, they will be able to act as a megaphone of the brand’s values ​​and services.

Of course, if you want to achieve this result, it is essential to adopt a collaborative approach by all company branches. If traditionally the data belonged to the CFO, now they are also related to marketing and sales, Industry 4.0 has made them a matter of logistics and production, and slowly they are also reaching human resources. All company functions are now “pervaded” by data. That’s why in the most successful companies, data and analytics are specific to each business unit with some degree of centralization.

 

Enrich your Data Lake with FAIR data

But what are the guidelines for making data matter every day, for all company branches? Let us remember that one of the most important aspects is to constantly enrich your database, perhaps by identifying third-party public sources, such as Google API, that can provide useful information on your business.

The important thing is that any company that aspires to become data-driven should make sure that its data is FAIR, that is:

  • Findable: the availability of data is one of the most difficult aspects especially for those companies organized in silos, which often lead to data repetition and a (usually) lack of coordination
  • Accessible: In highly regulated companies, it is important to ensure that access to data is done in a discretionary manner based on the rules and guiding principles of each organization.
  • Interoperable: interoperability, that is the ability of a system to cooperate and exchange data with other systems, is difficult to obtain because it requires data integration processes, but represents a great opportunity for companies that in this way they would be able to identify the most relevant sources.
  • Reusable: once the company has obtained the processed data, it is important that these can be used to their full potential.

 


 

Food for thought…

  • Here you will find the complete research of the MIT Sloan School of Management.
  • We have said that it is a data-oriented corporate culture that really makes a difference. Well, according to an Accenture survey, only 21% of employees involved in the research said they were confident in their ability to use data.
  • If you’ve just hired a Chief Data Officer, here’s everything he/she (and you) needs to know.

Interesting podcasts…

  • How do you survive in a constantly changing world? McKinsey talks about it in his podcast “Inside the strategy room”.
  • The world’s most innovative leaders in business, technology, government and education discuss the digital revolution and the impact on business and technology in the “CxOTalk”podcast.
  • And then there is “Atomi e Bit”, the podcast by Andrea Latino and Manageritalia.
Comments are closed.