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Four Steps Towards Creating a Data-Centric Organisation
August 18, 2021

By Dr Stylianos Kampakis, Expert data scientist and AI engineer
 

FP&A Tags
Data-Driven FP&A
Financial Planning and Analysis

dataData today is being created and consumed at an unprecedented scale. Data science is progressing even faster, further speeding up the rate of data creation and consumption. The companies that are the first to adopt the best practices will gain a significant advantage. The rest might just perish. 

But are companies taking this shift seriously? And more importantly, do they have the resources or the guidance to create, grow and nurture a data-centric organisation? If the corporate culture is up to the task, communication is clear and sufficient training is in place, financial planning and analysis (FP&A) teams can help their organisations improve the decision-making process significantly. What do we need for this to happen?

In this article, we demystify three buzzwords (data-informed, data-driven and data-centric) that CEOs must be aware of to ensure successful implementation across their organisation and we also explain how organisations can become data-centric.

What is the difference between a data-informed and data-driven organisation?

At the start, we have ‘data informed’. When we say that an organisation or a person is data-informed, it means that they are actually using data and the context of data as inputs into their conversation and decision-making process.

So, if you’re using things such as dashboards and key performance indicators (KPIs), for example, then you are data-informed. Nowadays, it’s very easy to be data-informed. You can use Excel or another simple tool and it’s not that difficult to make a few simple charts to see what’s happening within your organisation.

However, being data-driven means taking it to the next level. This is when you start using more intelligent algorithms and methods to get the data. Then you transform the decision-making process by using the algorithm to make the decision for you or by taking the algorithm’s output into account.

Obviously, being data driven does not mean that an algorithm needs to make every decision, but it does mean that you use algorithmic outputs in some parts of the organisation and in the decision-making process.

How can organisations become data-centric? 

Being data driven improves efficiency and can actually improve decision-making and it also fosters a data-centric organisation. 

data

There are four things to keep in mind to become a data-centric organisation.

  1. Improve your communication. This is an area where many firms and individuals go wrong. Improper communication gives out a wrong signal and can mess things badly, leading to grudges and fostering indifference between senior management and employees. Keeping employees motivated and aware can prevent miscommunications.
  2. Incorporate a data science culture. Fostering the right culture means top management and employees are in the same boat. This will enable you to maximise the impact of data science from the data collection phase to the research and application phases. That’s when you’ll start seeing some real results within your organisation. However, you will see resistance of three kinds here - cultural, personal and intellectual. 
  3. Organise workshops and reward good behaviour. It's not just about the bonuses, it can also be about the ego. Organising internal data hackathons once or twice a month or allow employees to play around with an idea of their own. Their unique insights can be published on a blog, or you make libraries and software open source and attribute the developers. For example, Google and Facebook have their own research blogs. Facebook also has a forecasting library called Prophet when you can read an article written by the people within the company who created the library.
  4. Keep the data scientist happy and well fed. Now don’t go and stock a fridge with food (that’s also ok), but feed their intellectual curiosity. Consider mentorship programs for new data scientists. Junior data scientists can be very enthusiastic, and sometimes you can find amazing talent from some good universities who might be a bit inexperienced. 

In conclusion

Finally, as you start to build your data-centric firm, keep the focus on how you can reward employees during this shift as everyone hates having to do more work with no reward. Alternatively, you could get in touch with us, and we can guide you.

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