Rafael
Rafael CRO @ FetchBug, basketball fan. Wine sorcerer and hype beast, official Jordan athlete (and customer).

What data should I use?

What data should I use?

Data, data, and more data. There is no single executive on LinkedIn or at any conference, that is not trying to talk about digital transformation, and of course, about data. We get it, data is king and everyone who wants to get a strong competitive advantage is going to need to use data, test data, discover new data, create new data, and do it all over again and again.

There is a big chance that we already know what we want to do with data, although the possibilities are endless and it all depends on the overall strategy your company is taking, there are several examples we are looking in different companies across industries, such as data for knowing our customers, our markets and our whole ecosystem; data for supply and demand; data for better logistics; data for it all. In the end, we know our use cases and we kind of know the results we can achieve if we start using real business intelligence, data analytics, and data science. But the real question is what data should I use?

What Do I Have?

Most use cases will need two or more sources of information in order to have better results, but first of all, we should look up the data we may already have. There is plenty of information that we already have and that we can start using to get a glimpse of the day by day operations of our companies. It does not matter the type of industry in which you are, there are four types of internal data that you will find on your company, those are sales, financial, marketing and human resources data.

  • Sales data: This type of data can help us understand areas of weakness and areas of strength, which may drive a shift in marketing, supply, or focus. πŸ’°πŸ€‘
  • Financial data: Unlike sales, which provide information about the number of products or services sold, financial data reveals what a company is spending to make these products and services, and the variance in those costs. This data can help to shift order cycles, to slash costs and boost margins. πŸ›‘πŸ’Έ
  • Marketing data: Marketing departments are a treasure trove of data. They can generate reports on customer behavior, customer profiles, social media campaigns, and more. Analyzing internal marketing data can help business owners decide which marketing campaigns are working, which ones need improvement and what type of new campaigns would be effective based on the needs of the target customers. πŸ‘¨πŸ‘©
  • Human resources data: This type of data is important in order to understand who the company is internally perceived, and it can reveal the areas where a company needs to improve its processes to make workers feel empowered and valued, and therefore more likely to buy in with their skills and talent.

There is a huge chance that you are already looking at this information on the different analytics or business intelligence tools your company has, in the end, looking at internal data is not something new or trendy, but it is good to know what kind of information your company owns before looking for more.

What Do I need?

Yes, internal data is cool and there are a lot of things you can do with it, but there is also the huge risk of being biased by it. There are plenty of other variables that happen on a day by day basis that affect your sales, your operation, your costs, your supply chain, etc. and if your models or analysis are done without thinking of this external variables, the results you get will always be the same: not trustworthy, exact, nor useful. There is a phrase I like that says β€œlooking at internal data is similar to looking through the rear-view mirror of your car”, in the end you only get a small part of the picture, a part that has already passed by, and what you don’t notice by looking strictly at it is that there is plenty of more to see.

And yes, we get it, getting external structured data is hard (even harder in emerging markets), and while some data is offered by federal agencies, this data it is not updated, trustworthy, nor reliable. There are also a couple of providers that can help you get a few data, but we don’t really believe you have to pay big for getting the data you need. In FetchBug we understand all of this, and we also understand that for a correct analysis you require different data sources ingested to your company in a way that actually works, that is why we have industry related dataframes that will help you get the data you need, the way you need it, making the adding external data to your company process, less painful.

What Now?

I am truly sure that businesses need to change the way they operate, analyze and use data, and while getting your data in order seems like a real challenge for all companies, the competitive advantage you can get by being smart with it is worth it every single time. The point of this article is to help you notice that getting a data practice on your company does not have to be so difficult. Yes, Data is King but you have to be willing to take risks and to understand that any data science, A.I. or tech initiative that your company has, is similar to any other initiative, it is all part of your whole strategy and it includes the risk of it not showing the results you expected. Data Science, Business Intelligence and Analytics are not magic, and while you may have the best tools and the best teams, if you do not have the correct fuel, you are not going to get the best experience.

In FetchBug we are happy to help you with any doubts related with data. I encourage you to comment and discuss this topic, feel free to reach me for a conversation on how we can help and remember that we do this for all customers, because in the end, they will be the ones who will benefit from all our initiatives.