The ‘Right Data’: What is It and Where Can You Get Some?

The ‘Right Data’: What is It and Where Can You Get Some?

By Irina Steenbeek, Founder of 'Data Crossroads' ​

In our earlier blogs we have discussed the role of data in your profession, your main benefits from proper managing of data, as well your main concerns about data. In this one I would like to give you a few practical tips on how to ensure getting the ‘right’ data.

So, what is the ‘right’ financial data? 

The survey by Prophix and FP&A Trends shows that only 12 % of respondents have access to the right data [1]. Reading this, my first reaction was: ‘but what is the right data?’. I did a quick ‘scan’ among my financial colleagues whether they knew the answer to the question ‘what is the “right” data?’. I was amazed by the wide variety of answers I received. Some mentioned more detailed data, other appealed to data of good quality or data that fit their purposes.

What would your answer be? Share it in the comments!

Of course, I have my own vision on what data is ‘right’, which is based mainly on my data management experience.

As a finance professional, you are responsible for delivery of information which can be used to support the decision-making process. You need to use data as an input in order to produce this information. In the end this is always a ‘supply & demand’ chain situation. So, it means that ‘right’ data to start with is data that would fit your eventual purpose. This is not the end of the story though, but just a starting point. Now you can start asking yourself questions, like:

  • How do I know what data would fit my purpose?
  • Who is responsible for the definition of the purpose?
  • Who can assess whether the data I have received would fit this purpose?

In order to be able to answer these questions, first, you need to understand who owns the data within your company.

Owning your data

Finance people very often considers themselves the owners of almost all data within the company and take on the corresponding responsibility. But is this the correct approach? Usually there are two main roles related to data. The first role is data owner. A data owner is accountable for the verification of data and managing data on its way from the owner to the data user. The data user is the role who is accountable for the correct usage of the data.

So now let us consider which of these roles Finance actually plays. 

Finance is definitely one of the most important users of data within your company. But is the finance staff accountable for data they receive? No. Finance only owns the new information they produce based on the input data. 

Assume you get information on a sales forecast from the sales department. They own the data they provide. You can challenge sales people on their predictions, but they remain accountable for the data unless you change it. 

So, if you are working in finance, here is my advice to you: stop cleaning data which is not yours! Go and look for data owners and let them do their job. 

Next, let us clarify the role of the IT department. Per definition, IT cannot own any business-related data. What they do is only providing their services on data delivery on behalf of data owners.

To get the right data being a data user, here are the only 4 things that you should do:

  • define your data requirements
  • set up requirements for quality
  • deliver these requirements to data owners
  • use data you get.

The first part: defining your data requirements is the trickiest one, let me give you some tips on what you should pay attention to.

Defining your data requirements

  • Provide a clear definition of required data.

You need to be precise in stating which data do you need from the beginning. You have to provide a clear definition. For example, you might want the ‘sales forecast per customer’.

Be careful, the sales department has their own language and might misunderstand your request. They might think you mean all of the existing clients and prospects, while you are talking about the customers who have purchased your company’s products in the past fiscal year.If you need go deeper and ask for sales forecast per product, it could become even more challenging. In some industries like financial services, financial, risk and commercial definitions of ‘products’ very often differ.

So, try to align these internal languages. My advice would be to start developing and using a company business glossary in order to speak a common language with your colleagues.

  • Stipulate a clear purpose of data usage.

Usually data users can tell you whether their data can be used for one or another purpose. For example, you want to distinguish customers per industry. You use NACE codes for this purpose. Still, check with account managers how they assign these codes to their customers. It might happen that their reasoning for the application of the codes differs from yours.

  • Indicate the required frequency and format of data delivery. 

You might need to receive the data daily, weekly or monthly. You might want to get it in Excel format in your mailbox or delivered in batch to your business planning software. Be sure to be clear on when and in what form the data should come to you.

  • Specify your requirements for data quality. I will come back to the question in one of my following blogs.

Being an influential stakeholder in this matter, gives you the power to promote the idea of defining data ownership and gathering data requirements. You can ask a colleague from IT or the data management team to assist you in specifying your requirements. The most important for you if to organize the process of:

  • gathering and summarizing the requirements
  • delivering them to data owners
  • checking that your requirements are fulfilled.

To sum up, you can assume that your ‘right’ data is the data that fits your purpose. All data that you get to work with is actually owned by other departments. You are only accountable for data that you produce. The most important thing for you to do being a data user, is to specify and deliver your requirements in a clear and comprehensive way.

More on this topic, and how you can improve the situation with data management in your company, your can read in my next blog.

Notes

[1] - ‘Defining the Evolution of FP&A: Benchmarks, Challenges and Opportunities‘ by Prophix and FP&A Trends, 2017. 

The article was first published in Unit 4 Prevero Blog

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