Advances in business technology since the advent of the PC have had exponential effects upon how entities budget, plan and report their results since the early 1980’s. Lotus 123’s (later Excel’s) contribution to budgets and forecasts is immeasurable. Thus, came the creation of “spreadsheet hell” that most currently active and experienced finance, accounting and IT professionals have come to feel is the norm.
The very best these early tools could offer was limited by how well we managed them and how well we hired the skills to leverage them. There has always been something of a trade-off between agility and reproducibility. This came down to individual’s skills in building and then managing these “black-box” systems. We loved them because they were built to our specific need. We hated them because they were generally the product of individuals holding moderately paying analyst positions, and these individuals were looking to move beyond these jobs. The knife cut both ways in the mid-90’s to mid-2000’s.
Oracle Hyperion has been a thought leader in this space since they developed Pillar. Hyperion Pillar had the flexibility of spreadsheets as their endpoint UI. It also had the central management capabilities of the administrator(s) consolidating within one application—where all the budget assumptions and calculations were warehoused and maintained. Hyperion trained administrators as well as their users. We thought we had plugged the weakness in the system.
Then came Hyperion Planning on-premises (or, now, Oracle Planning Budgeting Cloud Service). We broke our core reliance on spreadsheets, and embraced the power of Essbase Server. We also had scripts – powerful in their ability to build off of nested processes. With Hyperion Planning, we were even further away from homegrown systems and their risks.
Artificial Intelligence (AI): Thinking of the things we miss…
OK – what is AI? At its core, Artificial Intelligence (AI) replicates how humans think at a rate of speed and with quality and consistency humans cannot match. Embedded into AI are algorithms that recognize patterns, correlations, and which can then predict trends, events, etc. The promise of AI is that it makes the technology layer perceptively “less technical” to the end users. AI adds transparency to the data and automates tasks that previously required human interaction – and thus opened up the chances of errors.
Often, artificial intelligence technology is presented through the use of “bots.” These bots ask questions. Using lexical technologies, bots are able to understand how people in different professions, such as Finance, talk and write. Various bots are embedded at different points to ask the user what they want to do or where they want to go. This is used from the point the installation has begun and drives how the application will be laid out. It drives how the data will interrelate for meeting the specific needs of the enterprise. It helps define reports, alerts, rules, etc.
With these advanced technologies, Finance organizations are now at a pilotable place in the lifecycle of budgeting, planning, and corporate performance management (CPM) tools. Much like when spreadsheets “ruled the Earth” on 5 ¼ inch disks, and when we went from linked spreadsheets to Essbase, learning new software and predictive analytics will place immense power into the hands of the high performers and decision makers of your company.
How AI Is Changing Finance
Artificial Intelligence offers an incredible functional jump forward for Enterprise Performance Management (EPM). AI functionality means that the finance model can warehouse all our legacy institutional knowledge, and use it to learn more institutional knowledge. It can do this more efficiently and much faster than we ever could.
In theory, one could staff to a level where every transaction is reviewed individually. Realistically, this is highly unlikely – and it’s cost prohibitive. AI can review every financial transaction in fractions of a second. What’s more, AI can examine the relationships between these millions of transactions.
AI and Predictive Analytics
In addition to AI, we now have very powerful predictive analytics tools. The proliferation of R (a language and environment for computing and graphics) and its different flavors has turned IT report writers into defacto financial analysts. Period over period corporate performance in relation to the variables that effect this performance creates true, event-based predictive analytics. Using trending functions (linear, polynomial, etc.) is like throwing rocks at the moon, compared to a robust and well thought out R-based analytics package.
The power of these new tools greatly shrinks the effort of gathering data. We now have the real tools to shrink the work that goes into the true value-add effort of analyzing the data. AI sees the cuts of the data that highlight questions to be asked, so now we’ve got the technology to truly cut what we held aside as human value-add.
- Fast Deployment
- Controlled Quality of Data
- Extreme Flexibility in the Face of Change
What’s more, it places the deployment, feeding and caring of your finance applications with the stakeholders—Finance. There is minimal reliance on IT and other 3rd party services who you’ve relied on to support your Hyperion on-premises solutions.
Analysis is power. Its what keeps score. By leveraging AI and predictive analytics, you put the interpretation of data into the hands of the on-field players. This is especially so if you also leverage the cloud as the delivery platform. Cloud-based finance solutions deliver real time reporting of enterprise performance events before the financial consolidation and close—when there is a chance to respond with agility and facts.
Need help migrating to the cloud? Strafford has decades of experience in helping finance teams automate, align and optimize the financial solutions that will improve financial consolidation and reporting, budgeting and planning, and financial analysis. Hundreds of happy clients trust their finance ecosystem to Strafford.