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Finance Digitalisation - How to Get Started & The Benefits

By Christopher Devaney ACMA CGMA, Senior Strategic Finance Analyst at Intel Ireland

What is Digitalisation?

In this context, we are looking at “Digitalisation” through the lens of the Finance function. However, the benefits of Digitalisation stretch far beyond the Finance department and right to the bottom line. Digitalisation for Finance is, basically, the advancement of capabilities due to integration of new tools & technology into the culture. Depending on where a given company is on their ‘digitalisation journey’, this could mean the introduction of new accounting software, automating month-end close processes or incorporating AI into the accounting process.

Finance Digitalisation at Intel:

At Intel, we are fortunate to have a dedicated Finance team “DARC” (Data Analytics Reporting Centre of Excellence). They’re demonstrating by example and partnering with all finance teams around the company to Digitalise Finance and empower all our Finance employees to play a part.

Structure:

The DARC Finance team has expanded significantly in recent years, comprising of predominantly people with data science backgrounds. There are international reps, including myself, who represent finance departments for major Intel sites around the globe and act as a key link to the DARC team. The group is structured using a hub and spoke model and this allows the team to work with Intel leaders in different areas and ensure there is a team dedicated to each spoke. DARC isorganised so that each spoke is a key facet of the P&L or balance sheet:

Citizen Data Scientists:

A Citizen Data Scientist is defined as somebody who possesses the skills of a data scientist, but it is not their primary role. There is a huge benefit to training and equipping finance employees with data science skills and tools. By taking existing finance skills, such as integral business acumen, and marrying them with data science skills you create a sweet spot. This is exactly where your finance team needs to be. This allows finance professionals to speak the same language as I.T. professionals, leading building models, dashboards or automated processes by simply acting as Citizen Data Scientists.

“If all of our data scientists were in I.T. , we wouldn’t be getting the benefits we are seeing today”

Vivek Patel – Director of Finance, Data & Analytics at Intel 

How to Get Started:

Leadership Buy-In


The best way to get started on this journey is to prove the value of data science with a small example. After proving the value on a smaller scale, it’s critical to secure senior management buy-in to invest for the long-term. It’s not enough for leaders to only talk about “Digitalisation”. Instead, it’s necessary to talk about what will be done and set clear expectations. It’s not enough for senior management to agree and support the initiative if the culture will not change.

Training

The first action any organisation should take is to train its people in Data Science. It’s become increasingly prominent that that finance job roles are increasingly seeking Data Science skills and experience with Python, SQL, Java, Tableau or PowerBI. In 2019, CNBC reported that “job listings requiring these skills in the financial industry increased nearly 60% over the past year.” As such, there are many courses available online such as “What is Data Science” by IBM via Coursera & the Digital Mindset learning pack from CIMA to begin a Data Science journey.

Culture Shift

Becoming a “Digital first” Finance organisation takes a culture shift. One which will not take place overnight. It is hard to let go of trusted excel spreadsheets and it takes a leap of faith to have full confidence in a new, automated tool. Ensuring training is in place will help to overcome any resistance to change and increase engagement with new the ways of working. It can also be useful to offer incentives for teams to implement digital practices, such as automation or dashboards to create momentum for this culture shift. 

Planning

A well thought out strategy and plan of action will save time and money in the long run. Start by identifying the largest pain points or longest processes in place today. Identifying the appropriate tools to improve and making the right selection is critical. It is important to map out all the given data inputs, processes and outputs to ensure that the data is not misconstrued or misreported in any away. 

Basics

To reach the point of ‘real-time data’ at scale requires a strong level of proficiency in I.T. It is also possible to get the basics right and start with focusing on specific aspects e.g. headcount figures. The basics include ensuring input data is accurate as the starting point and that one set of data is used by all parties known as a “Single Source of Truth”.  The data will need to be structured into a format that can be easily read by a program such as PowerBI. 

Format

A crucial aspect to the data format is to ensure that it is structured with columns, rows, and table headers. This will allow a visualization tool to read the data correctly. This allows you toshare the data with your colleagues whilst maintaining control over access there are many tools such as Dropbox, SharePoint or Microsoft Teams. It’s critical to check the privacy settings and only allow read or edit access to those who require it. 

Shared Examples

Seeking examples of ‘Digitalisation’ within your network and finding out how other companies are implementing digital tools in Finance can be very powerful. This is a sure way to see a tangible example of what is possible and if you can share this with your team, it will get the creative juices flowing!

Benefits of Digitalization in Finance:

Automation & Cost Savings:


“Transformation is no longer about simplification; true automation is about increasing density of detail available at a faster rate”

Kyle Schlabach - Enterprise Finance BI Controller at Intel

A key quick win is the automation of routine tasks. This saves time and allows you to focus more time on higher value-add scope. By setting up predictive analytics and visualization tools this will drive more valuable discussions with all stakeholders.

Caveat emptor! Be cognisant that automation is not about removing key details or layers of info which can often come due to process improvement. True automation is about increasing the amount of detail and increasing the density of information available at a faster rate. In previous finance transformation across industries, there was a desire to improve businesses processes. However, it often meant sacrificing key details down the line. 

Globalisation:

Data stored in the cloud enables the hiring of employees from anywhere in the world with the required data science skills needed as they can access the data remotely. This trend has accelerated due to the Pandemic and increased flexibility around remote work. 

Real Time Insights:

Finance Departments act as the custodians of data for many businesses across industries.  One of the largest benefits of digitalisation is the ability to offer real-time accurate data to help make faster decisions and reduce missed opportunities. The traditional concept of budgeting cycles and financial close is moving towards real-time reporting. Investors and directors around the globe are starting to ask for more frequent updates as a result. A sure way to impress investors, business partners and company leaders is to deliver information via real time dashboards and insights. It also allows for collaboration between finance and key stakeholders at a more strategic level reducing time spent gathering the necessary data to begin the conversation.

Risk & Controls:

Today there are an abundance of companies offering software to help with financial controls using algorithms and training data sets to analyse statements, detect fraud and calculate different types of risk. The tools available today can help calculate risk by analysing existing data and running specific queries to determine risk such as credit worthiness or currency risk. For example, “Working with one major credit card company, Scienaptic boasted $151 million in loss savings in just three weeks.” By implementing their AI and digitalized platform. Schroer, A. (2021)

Increased Efficiency & Margins:

There are many examples in everyday app’s on our phones where businesses are increasing margins due to digitalization and implementation of machine learning. Machine learning is applying algorithms using neural networks or deep learning on very large, fluid, and evolving data sets known as Big Data. Take Uber for example, by reviewing historical data demand can be forecasted more accurately and supply can be increased by notifying drivers of peak times. The marginal price increase during busy periods encourages more drivers to come online to meet the customer demand and leads to more satisfied users which is all driven by algorithms. Uber also apply machine learning techniques for route optimization, single-click communication with drivers and organising Uber Pool.

It is possible to apply the same type of principles within any business. For example, take a clothing retail store selling high street fashion. By setting up real time data dashboards for in-store sales you can start to draw a picture of which days sell the most product, which stores are selling certain SKU’s and react faster to ordering more/less stock as a result. For example, Zara include pricing for all countries on their clothing items and will ship product around the globe if they see that certain products are selling better in other markets.

Best of luck on your Finance Digitalisation journey! 

The Digitalisation revolution has already begun. Those who adopt it early and engage in a strategic fashion will reap the rewards. The Finance Function is perfectly positioned for the opportunity to be the driving force behind digitalization in their business and ultimately increasing the bottom line for shareholders.  

About Christopher Devaney: 

Senior Strategic Finance Analyst at Intel Ireland. Experience to date at Intel spans from Finance Business Partner to Movidius Artificial Intelligence R&D team, Financial Accountant for manufacturing operations and Management Accountant for Capex team leading a forum of global analysts to deliver savings and improve forecast accuracy. Winner of Susan O'Neill Award 2018 - This annual award is the highest award in Intel Ireland Site Finance; it is intended to recognize strong contributions through exceptional behaviours. The award is based on nominations from members of the Ireland Finance team.

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