Financial data is an essential part of any good companies’ data portfolio. Through proper data
analysis, you can deliver more to your shareholders and do a better job as a CFO. Modern data
analysis has changed the business landscape by a considerable margin, as financial analysis
itself is getting more sophisticated by the day.
Through proper financial data analysis, you can significantly augment your efficiency, internal
performance, and cut down on costs of operation. In this article, we’ll give you some tips on
improving your financial data analysis so you can reap these benefits.
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Understanding the Data
Any good CFO’s job starts with understanding the financial data that goes through the analysis
process. Understanding the financial data is as essential as the process itself because, with the
improper data, you’re not going to get any accurate results.
When money is concerned, working with accurate data is essential if you’re looking to make
accurate predictions. Making fair assessments and predictions with incorrect data is virtually
impossible, and inaccurate data itself might cause your company to hemorrhage money.
Data is a relatively simple thing, and the data analysis process is relatively simple as well. Data,
in its initial form, is known as raw data. Raw data includes all of the data accumulated in one
way or the other, which doesn’t necessarily have to be accurate.
Raw data is beneficial, but not for analysis. It isn’t the ideal candidate for analysis as it is chock
full of situational data, redundancies, and fake data that come courtesy of the data collection
process. To remove these negative characteristics of raw data, it has to go through an intricate
refinement process.
The data refinement process eliminates all the negatives from data, which leaves you with
accurate data to use for your analysis.
Adequate Research
While relatively simple to comprehend and understand, the financial data analysis process is far
from simple in practice, and that is because a hefty amount of research backs up any useful
analysis.
To help you get a picture of what research needs to be done before the financial data analysis
process itself, we’ve divided it into four simple steps.
1# Identifying the Market Metrics
Research is virtually synonymous with identifying the proper metrics. Based on your unique
business model or your industry, different vital metrics are going to vary. Finding out what the
standard is for other businesses in the same industry will give you a proper perspective on what
your business should be doing.
Data garnered from identifying the industry standard will be full of flaws and needs to pass
through a refinement process to use further.
2# Assessing Internal Company Performance
Just like identifying what your competition is doing, you’ll have to accumulate a detailed
account of your internal company performance. Taking financial statements, KPIs, and
achievements into account will give you critical data on your internal company performance.
Data garnered from identifying company performance doesn’t always have to be accurate due to
variations, timeframes, and redundancies. This type of data also has to pass through a
refinement process before further use.
3# Accounting for The Ratios
The main thing you need to consider when garnering data from your business and other
businesses is the ratios. There are a lot of proportions that go into play when you’re assessing
data and comparing them.
You’ll have to account for the liquidity ratios, which present the timeframe in which your
company translates assets into money.
On the other hand, solvency ratios show how companies handle their long-term commitments,
such as assets production.
Lastly, you’ll have to take valuation ratios into account. They give you a proposed future value of
the stocks and assets within a company.
Accounting for these assets and scaling them to your business’s size will give you an accurate
perspective on your business performance.
4# Comparing Your Business
Lastly, to tie up the whole research process, you’ll have to compare your business to the industry
standard. That will give irrefutable data that needs to go through little to none refinement to be
accurate for further analysis.
Utilizing the Tools
Financial research isn’t as straightforward as other types of research, and keeping up with the
market trends could take a considerable amount of time. Accumulating, refining, and analyzing
all the different data is time-consuming, significantly because the information is frequently
changing.
To ensure you’re always on top of the situation, you’ll have to utilize the right tools for the job.
The digital revolution has streamlined many-a processes that used to take a lot of time, and data
analysis is one.
Many data analysis programs help you increase the efficiency of your financial data analysis and
programs that work in real-time. There is a wide variety of tools you can use for data analysis,
such as:
Data Collection Tools/Crawlers
Data collection tools are available all across the web, and depending on the sophistication, the
prices will vary wildly. Data crawlers search the web for all relevant data. They’re completely
legal and are very viable tools in any data analysis arsenal.
Data Refinement Tools
For a CFO to make an accurate prediction, he is going to need fantastic, accurate data. All the
data collected by crawlers is considered raw data and has to go through a vetting process that
removes all invalid data. Data refinement tools are customizable for your unique specifications
and do this perfect, and they’re readily available across the web.
Data Analysis Tools
When it comes to data analysis tools, things are far more complex than merely downloading the
first thing that pops in your search results. Financial data analysis tools, while available, can cost
a lot of money, and developing in house tools for detailed analysis could cost even more. Using
financial data analysis tools, a CFO can streamline the analysis process and have more accurate
results more frequently.
Data Visualization Tools
The last step of the process is data visualization. Putting your data in a visual medium will make
it easy to understand, digestible, and presentable. You can visualize your data by any means, and
there is free software available on the internet. Data visualization is very applicable, as it works
with all sorts of data and presents it. Some of the most popular types are:
- Comparative
- Temporal
- Composite
- Spacial
- Distributive
- Organizational
- Relational
Final Thoughts
Financial data analysis is an essential process if you’re looking to up your game as a CFO and
make correct assessments about your potential business prospects. With so many tools readily
available, streamlining this process has never been easier, and with just some research and
effort, you can potentially increase your profits by a considerable margin!
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