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Technology for Finance Transformation

Key technology trends for finance transformation
University Business, December 2017

Transforming finance to meet the challenges of processing more information efficiently and turning that information into deeper insights is an organizational imperative. These transformation initiatives are also focused on minimizing non-value add work, decreasing reporting cycle time and improving collaboration.

This webcast discussed how finance teams are turning to the cloud and digital tools to address these challenges and take their processes into the future. 

MIKE ROST

VP of Corporate Marketing 

Workiva

Mike Rost: Taking a look at reengineering finance processes, we are seeing two drivers. First is digital disruption—we see organizations moving toward digital information, robotic process automation, the cloud and new self-service analytic tools. Many of the current tools that teams have been using for the past 10 to 30 years do not scale to provide the most efficient process. We see a lot of firms reengineering processes for greater efficiency and to free up funds for investing in further value-creation activities. Finance departments must deliver value to the organization. Performance management brings value in the areas of strategy, key performance indicators and cost reduction. Improved performance management will also make the finance function more agile.

The second driver is either IPO readiness or managing financial transactions. This year we’ve seen a drastic increase in companies going public. In addition, recent stats show there were 3,000-plus mergers and acquisitions in the U.S. economy this year. Whether you are buying or selling companies, or going public and through some sort of capital transaction, you need to have your house in order.

There is a burden that’s put on a lot of organizations in the collection of data and on top of the transformation imperatives to adopt weekly and monthly performance reporting. In a lot of transformation initiatives, organizations are driving both the volume and the complexity of the types of reports that they’re managing and of the data they’re collecting.

Mike, when we look at this from a transformation side of things, how is current technology ready to address those sorts of increased reporting requirements and increased reporting complexity? 

Speaker 2: The first thing we want to talk about is some of the technology shortfalls of today’s legacy systems—in particular desktop spreadsheets, the most popular being Excel. I’m not attacking Excel as an individual productivity tool, but when we start to email Excel files around and try to collaborate with people, that’s when the trouble starts. Spreadsheets work fine for individual tactical projects, but fall short for any kind of robust planning or collaborative reporting. The problem is usually magnified when you try to use spreadsheets to manage data, especially with a larger group of people or across departments.

In addition, Excel and other desktop tools have some security shortcomings. It’s hard to restrict access to just authorized people, and it’s hard to track who has made changes and to what, and it’s hard to ensure that the data is not used for the wrong reasons. Another key shortfall is data integrity and quality—errors in formulas and in processing, and having the wrong values from the wrong people in that whole aggregation process. There’s also the issue of version control; how do you know which version is the truth?

Also, we want to be boosting the intelligence of data. The more metadata and tagging and understanding that can be included with the data—whether it’s attaching evidence or supporting documentation—the more intelligence you’re going to have in that data. Certainly none of that can be done in Excel. 

Mike Rost: There are other tools too that sit inside the finance value chain—transactional systems, a general ledger, accounts payable, a broader ERP system, or some sort of VI, or even corporate performance management tools. Each of these has its purpose, but we see a lot of organizations struggling when they try to extend the use of those tools into something they’re not necessarily designed for. There’s a transformation opportunity in utilizing something that glues those things together in a more cohesive way.

Collaborative work platforms provide what we call a “unified data experience”—a single, centralized platform for data that’s owned by the finance team, not by IT. That data set is going to provide real-time insights into your organizational performance—anything from a historical financial report to a forecasting budget. The collaborative work platform also provides improved control over processes, particularly to mitigate risks. This type of integrated reporting lets you connect to data and documents and delivers a continuous and comprehensive audit trail. So you’re always covered from a standpoint of who has access, who has made changes, and all those things around data and reporting governance.

The key software requirements for a collaborative work platform are that it needs to be cloud-based, needs to be an integrated data experience platform, needs to have a repeatable reporting framework, and needs to provide access via a phone or tablet.

To support these finance transformation initiatives, we want to get to what we call “smart data.” Part of that is just being able to layer metadata, attach things, and work with it that way. The goal is always having data that’s relevant, so that it’s information that makes a difference, especially when you’re trying to make projections or predictions. 

Speaker 2: One of the things that often comes up with a lot of companies is what I frame up as composite reports—those reports that end up being a combination of narratives and descriptions along with charts and graphs and tables of numbers. 

Mike Rost: That’s the key to this type of reporting—being able to first stage all of the financial, operational, sales forecast and planning numbers in this centralized, as-reported data store, and then have the ability to identify where you need to have key data linkages. The idea is that you build this one single source of this as-reported data and you’re able to link out from that source into multiple reports. That has to be supported, whether it’s a document format, whether it’s a presentation format, or whether that number is appearing in a tabular format within the report.

To watch this web seminar in its entirety, visit www.universitybusiness.com/ws101817 

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