Becoming a valued strategic partner: Data-driven finance comes of age
The Hackett Group and EXL join with top tier clients to discuss global business services as an enabler to data-driven finance
As organizations continue to expand globally, they are increasingly challenged to address regional accounting practices and procedures, cost and wage structures, employee turnover patterns, third-party service providers, and disparate systems across the enterprise. How can finance organizations stay on track of all this and become valued, trusted advisors to businesses? What technology and transformation alternatives are available to help facilitate consistent, efficient financial reporting, alongside the greater vision of strategic value-creation through informed decisions?
Top finance organizations, including those behind the leading brands featured in this discussion, are already transforming to meet the future through digitalization and tapping into expert global talent pools. In a recent executive roundtable conducted by The Hackett Group, a leader in business advisory, benchmarking, and transformation consulting services, and EXL, a leading data analytics and digital operations and solutions company, the value of Global Business Services (GBS) as an enabler to data-driven finance was discussed in detail. What follows is a recap of the discussion.
A tale of two transformations
The roundtable kicked off with two case studies presented by a global media and large insurance company, both based in the U.S.
The media company’s journey
The company’s vice president of operational transformation, automation, and AI shared with the audience his organization’s transformation journey from 2008 through the present, highlighted by the creation of an enterprise program to accelerate growth and provide scale through using a strategic provider of finance function operations in 2015.
The company adopted a global shared services model hosted on a single platform to accommodate consistent, centralized processes measured by RACI and ROI impacts. “The goal was to perfect our finance practice horizontally across our businesses and agency portfolio to improve efficiency, speed, and intelligence,” said the executive. “We lifted the burden off our internal staff and used data, automation, and analytics to enhance our efficiency and throughput.”
Currently, the media firm is partnering with EXL to scale several pilot programs across the enterprise globally, involving generative AI, machine learning, and intelligent automation to accelerate its progress toward a more streamlined, responsive, and intelligent finance function.
The insurance company’s journey
The company’s senior vice president of enterprise transformation and solutions presented his firm’s strategic rationale for building a GBS capability aimed at combatting inflationary pressures, creating an expense advantage, and investing in needed capabilities to drive profitable growth.
Starting in 2018, the firm began leveraging EXL for its finance, risk, data, and analytics capabilities in multiple global markets across legacy core and administration systems. Since then, EXL has expanded their GBS footprint to encompass customer contact, claims management, distribution, and product development activities.
“We are now in the process of consolidating our finance technology on SAP, with Anaplan web-based software and Microsoft Power BI used for business planning,” said the executive.
Since the transformation began, the insurance firm has lowered its finance overhead by more than 30%. The company is now pursuing continuous improvement projects to enhance global regulatory compliance and further enrich financial planning and analysis activities.
Five key areas to consider:
Following the opening use cases, the panel outlined five key areas for successful GBS transformations based on questions from the audience, as follows:
1. Transform mindsets before you transform the system
Resistance to change should be expected, especially when it spans entire departments accustomed to legacy systems and the way things have always been done. For this reason, early buy-in is a base requirement for transformation. Those leading the transformation should prepare a detailed use case, including objectives, timeline, budget, responsibilities, metrics, and expected ROI for executive approval. Group leaders from across the organization should be assigned roles, to ensure broad engagement with the plan. All parties affected will need to be alerted and updated early and often throughout the process. If necessary, outside change management experts should be consulted to ensure enterprise-wide acceptance of the program and minimal disruption.
2. The biggest challenge: Getting the data right
Considering that automation will play a major role in your GBS program, ensuring that you have clean, reliable data will be job one. The axiom, “garbage in, garbage out” is on point. ERP data will drive consistency across the system, but other data layers will come into play. Determine a common, central repository for all your data, prioritizing its preparation according to the value use cases you considered when building your transformation roadmap (i.e., collections first, cost of accidents second, regulatory reporting third, etc.). External data will naturally be the most suspect category but don’t simply trust your internal data either. There will be gaps and you will need to investigate ways to fill those gaps as you proceed.
3. Automate according to priorities
Automation, as a scale-enabler, encompasses a broad array of solutions, including both off-the-shelf and bespoke tools and technologies. The question is, “Where do you begin?” Review your transformational roadmap. Determine what discrete components you need to create a minimum viable product (MVP) and expand from there. Consider what components can be reused in other areas of the organization. For instance, a reconciliation bot may be the ideal time-saver for financial operations, but with a little modification, IT can also use it to reconcile data files.
Another area to consider is generative AI. Generative AI is a technology that is here to stay and is already a useful tool in business (i.e., ChatGPT in front-end conversational applications). Its efficacy in other business areas is growing fast. You can effectively train the technology to support human efforts by uncovering new intelligence hidden within your data. For instance, a model can be trained on multiple sets of corporate data within an organization to help plan for various business scenarios.
Use cases such as this one are starting to sprout up in finance departments worldwide, and EXL is helping to successfully implement them. For instance, the featured media client cited experiments using generative AI to partially assemble timesheets based on departmental output.
The main caution (at least, at this point) is to validate the output for accuracy. With care, a bot can improve performance from 70% accuracy to 90% in a relatively short period of time. And, while a quality model may not do all the thinking for your people, it can ultimately compress the time and effort it takes to complete a process significantly.
4. Apply technology to enhance talent investment
No GBS journey progresses far without addressing the human side of the equation. The whole purpose of automating is to free up time and money to accomplish more with your available talent. That may include reducing overhead for other necessary investments or refocusing team members to improve performance in other areas of the business. In the use cases discussed, this was accomplished in two ways—through automation and partners able to provide the right talent.
EXL helped both clients adopt the automation solutions they needed to elevate human efforts, relieving staff of cumbersome, repetitive tasks so that they could learn new skills or spotlight efforts on more value-producing priorities.
5. Strive to inform organizational strategy
In the end, a successful GBS transformation will elevate the finance department to a more credible position within the enterprise, moving from necessary reporting functions to weighing in on the strategic matters that shape the company’s future direction. The insurance client, for instance, used Anaplan and Power BI to provide the finance team with the story-telling narratives they needed to steer decision-makers toward new markets, products, and services. By streamlining hundreds of reports from dispersed offices across the organization onto a single, self-service dashboard for review, company executives are now seeing patterns and gleaning insights instead of compiling complex reports.
Find out for yourself
To discuss your immediate transformation plans and explore how you can achieve a data-driven finance function now, contact us at www.exlservice.com