Advanced Analytics
Introduction
01
advanced analytics
But despite all of the potential of advanced analytics such as predictive analytics, machine learning and financial signaling, adoption amongst Finance teams is still low.
In fact, according to the Dresner Advisory Wisdom of Crowds® Data Science and Machine Learning Market Survey, less than 20% of finance teams are deploying these technologies today.
OneStream’s Guided Workflows protect business users from complexity by guiding them uniquely through all data management, verification, analysis, certification and locking processes. Users achieve financial data quality management and verification through standardized and simplified data collections and analysis with reports at every step in the workflow. Guided Workflows provide standard, defined and repeatable processes for maximum confidence and reliability in a business user-driven process.
Will advanced analytics eliminate all the uncertainty in the world today? Absolutely not. Nor will these technologies change the Office of Finance forever. Does it mean that all of today’s decisions will be automated away? No. Should Finance teams expect 100% forecast accuracy all of the time. No. Does it mean that all legacy planning processes should stop? Absolutely not.
Advanced analytics offer Finance teams a new way to ask “why” and drive performance. But like with any other new technique or technology, it’s critical to sift through the hype and try to understand “what this means for me.” No solution will offer the perfect forecast or answer every question that CFOs or CEOs ask. However, if finance leaders can take one small step forward to evaluate advanced analytics through the lens of being an enabler for Finance, like we've done for hundreds of organizations around the globe, OneStream can help your Finance team take giant leap forward.
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Like the increasing adoption of cloud-based solutions by finance, the adoption of advanced analytics is a matter of when—not if.
Finance teams not only require tools that help collect and organize large volumes of operational and financial data – organizations need to actually leverage this data to create insights for decision-making. The COVID-19 pandemic is creating new pressures for CFOs and Finance leaders to finally break the month-end reporting cycle. Why? So their business partners have the ability to take mid-stream actions on daily or weekly financial & operational signals that impact financial performance—before month-end.
06 Bringing It All Together
05 OneStream’s Innovations in Advanced Analytics
04 Helping Finance Lead at Speed
03 The Power of Advanced Analytics
02 Advanced Analytics in the Office of Finance
01 Introduction
06 Bringing It All Together
05 OneStream’s Innovations in Advanced Analytics
04 Helping Finance Lead at Speed
03 The Power of Advanced Analytics
02 Advanced Analytics in the Office of Finance
01 Introduction
06
05
04
03
02
01
The Power of Advanced Analytics
03
Advanced Analytics
Helping Finance Lead at Speed
04
ADVANCED ANALYTICS
OneStream’s Innovations in Advanced Analytics
05
ADVANCED ANALYTICS
Bringing It All Together
06
ADVANCED ANALYTICS
Companies that characterize themselves as data-driven and are in the top third
of their industry
are 5% more
productive and
6% more
profitable than
their competitors.
In the Office of Finance
02
advanced analytics
Addressing the Challenges
03
ADVANCED ANALYTICS
Addressing the Challenges
03
ADVANCED ANALYTICS
Business Challenges
02
ADVANCED ANALYTICS
Introduction
01
advanced analytics
Planning, budgeting and forecasting in today’s global economy requires organizations to be prepared with the ability to respond quickly to new market opportunities or threats. The increasing pace of change in business is putting more pressure on Finance organizations to improve agility and to better align Finance and operational plans.
Success requires the ability to set corporate targets or budgets, combined with the ability to continually monitor performance and
Case Studies
05
ADVANCED ANALYTICS
Did You Know...
But despite all of the potential of advanced analytics such as predictive analytics, machine learning and financial signaling, adoption amongst Finance teams is still low.
In fact, according to the Dresner Advisory Wisdom of Crowds® Data Science and Machine Learning Market Survey, less than 20% of finance teams are deploying these technologies today.
OneStream unleashes the power of Finance by unifying planning, financial close & consolidation, reporting and analytics through a single, extensible solution. We empower the enterprise with financial and operational insights to support faster and more informed decision-making—all in a platform designed to continually evolve and scale with your organization.
OneStream’s comprehensive platform helps Finance teams access, maintain, validate and visualize data all within a seamless and unified experience. And in doing so on both governed financial and high-velocity operational data, OneStream provides a foundation for Finance-owned transactional analysis, reporting and sharing predictive insights—to find new ways to ask "why."
operations Finance
Sales
Finance
Corporate FP&A
Set targets for AOP and long-range plans
Validate forecasts from business partners
Seed baseline forecasts with predictive models
Create daily or weekly signals on sales, gross margin and working capital drivers
Industry / Mkt. Volatility
Poor Calculations and Drivers
Ineffective
Tools
Lack of
Data Access
Lack of
Mgmt. Input
50%
40%
30%
20%
10%
0%
Impacting Factors
When asked what factors were impacting their ability to produce more accurate forecasts, Finance leaders noted a lack of line management input and accountability (39%), lack of access to necessary data (38%) and ineffective software tools (32%).
What's Holding Us Back?
39%
38%
32%
29%
29%
OneStream’s Beyond the Hype Survey notes several factors, which are:
To evaluate the value of advanced analytics, Finance teams should ask themselves a few simple questions. Do we want to spend time building models or spend time interacting with them?
Advanced analytics in Finance is just like other corporate performance management (CPM) processes such as planning, financial consolidation and reporting. If Finance teams spend all of their time moving data, reconciling data and building reports, they’ll have no time to leverage this data to guide key decisions. But by leveraging technology to handle the hard work, Finance teams can shift a larger portion of their time to value-driving activities
such as forecasting cash or evaluating key capital investment decisions.
Leveraging Advanced Analytics in Day-to-Day Processes
Creating value from advanced analytics in Finance requires a similar approach.
Within Finance processes, advanced analytics can play a powerful role in driving collaboration and effective decision-making. Consider the CPM
framework (see Figure 1 to the right). While there are several versions
of this framework, most consistently show the role finance plays in
steering organizational performance as a continuous cycle of
mapping key strategies into actionable business plans.
What if you had the power to incorporate advanced analytics into these key processes, and do it directly within your day-to-day business processes? What if you could conquer the complexity of gathering and organizing financial and operational data or creating and maintaining predictive forecast models?
Brand
Finance
Sales
Finance
operations Finance
Corporate FP&A
Brand
Finance
Seed S&OP processes with predictive forecasts
Create financial signals on daily and weekly customer AR analysis (DSO)
Review daily and weekly customer pacing on unit volume or orders for top customers
Analyze future labor and material costs with predictive models
Create daily or weekly operational signals on controllable cost metrics
Track daily production and capacity pacing vs. plan and run rate
Extend predictive forecasting by store, brand, department, product category
Analyze daily and weekly trends in campaign performance
Analyze and optimize weekly pricing and product mix trends
Financial Signaling is critical to help Finance teams to move ahead of the monthly reporting cycle by leveraging the Financial intelligence that’s core for their monthly financial processes such as hierarchies, dimensionality, translations, FX rates and blending it with higher-velocity financial transactions and operational data from multiple sources.
With this unique capability, Finance teams can begin to analyze these signals on a weekly or even daily basis to compare how their key metrics and KPIs are pacing vs. their forecasts and run rates for the month.
This includes information on suppliers or customer orders and shipments, as well as core financial data around working capital metrics, marketing analytics, sales pipeline or operational performance.
Financial Signaling: The Next Inflection Point
With the sheer volume of data available and advancements in CPM software, Finance teams now (finally) have the capability to interact with advanced analytics. And do it at scale. How? Instead of taking on the burden of building models, Finance teams can rely on purpose-built software to help them supplement their analysis, reporting and planning processes with high-volume operational and financial signals, and with statistically significant, predictive forecasts.
Predictive analytics provides the power to predict future performance based on applying predictive algorithms to historical data. This is not new. But by automating model creation and deployment directly within CPM processes, predictive modeling is easy to execute for any planner.
This “ease of use” makes predictive models incredibly powerful for Finance teams.
Predictive Analytics: Low Cost & High Value
For Finance teams who need to go beyond traditional predictive analytics, ML is the answer. ML is where people and technology come together. For example, consider a retailer’s demand forecast for Product A in Region B within Store C. To forecast at this granular level, there are so many other factors at play. How about the weather in Region B, for instance? And what if Store C built a new parking garage? Or what if a major competitor opens a location across the street or changes their pricing? Factors like these are all potential features an ML model might consider if your Finance team has made the necessary investments in data scientists.
Compared to predictive analytics, ML comes at a higher cost and is harder to scale. But if your organization is committed to the investment, there’s a higher reward in terms of forecast accuracy.
Unlimited Forecasting with Machine Learning (ML)
TOP
THIRD
And for those organizations seeking to take their advanced analytics journey even further, OneStream is investing into ML solutions that will unify the most sophisticated analytical models with everyday CPM processes.
Machine Learning
Predictive Analytics
Analytic Blend
MACHINE LEARNING
PREDICTIVE ANALYTICS
Analytic Blend
OneStream’s vision is to provide an accessible ML framework for our customers that’s unified with corporate performance management (CPM) processes.
Extends analytic capabilities by applying statistical models to generate predictive forecasts leveraging the same data within a single, unified platform. Downloadable from the OneStream MarketPlace, Predictive Analytics 123 automatically generates high-predictive forecasts by leveraging 10+ built-in model types. The software runs hundreds of variations on your data and automatically reveals which of those models is optimal for you to use. Users can deploy and incorporate predictive models anywhere across the OneStream platform including workflows, all planning processes, reports and dashboards.
Enables customers to blend governed financial information with detailed operational data in the same analytic model. By leveraging and reusing OneStream’s core financial intelligence, Analytic Blend ensures that even the most granular operational data across our lines of business and functional teams are always in sync with governed financial hierarchies. And by combining analytics and transactional data too, Analytic Blend gives Finance teams the unique ability to provide Financial Signaling on weekly and even daily data to drive performance before the month-end close.
The Financial Intelligence to Make Mid-Stream Decisions That Can Impact Month-End Results
Financial Signaling in Action
Analysis
Management Reporting
Operational Plans
Financial Plans and Forecasts
P&L, Balance Sheet and Cash Flow
Consolidated Actuals
Monthly Financials
Days Sales Outstanding (DSO)
Working Capital
Customer Churn
Orders and Shipments
Supplier Performance
Daily / Weekly Operational & Financial Data
ML 123 (see Figure below) – will provide powerful and seamless integration with data scientist projects and link that back into core finance processes.
For organizations with data science resources:
Leverages our advanced data preparation engine to assist with feature engineering, such as incorporating gas prices, weather patterns and the impact of holidays.
STEP 1
Integrate data from Step 1 with OneStream’s ability to integrate with 3rd party ML platforms to allow data science teams to use their tools of choice. For example, Figure 3 illustrates OneStream’s integration with Azure ML.
STEP 2
Finally, integrate the output from the ML models back into the OneStream users’ workflow, enabling data scientists to deliver ML models directly into the planning and reporting process.
STEP 3
Sensible ML – Sensible ML is a planned OneStream Marketplace solution currently in development. What will it do? Sensible ML gives finance teams the power to leverage ML models without the data scientist. How? By guiding users through each part of the ML model building and deployment process, including feature engineering through advanced algorithm configuration, training and deployment. Here’s how it works:
For organizations without data science resources:
Data Load and Tagging: Sensible ML gathers information about the columns in the source dataset and other additional data (such as geographic data) from users.
Forecast Horizon and Scheduling: Users are prompted to input their proposed forecast horizon.
Baseline Model Comparison: Sensible ML compares ML models with traditional forecasting methods, like grossing up prior-year results, to calculate incremental forecast accuracy.
Feature Generation/Engineering: Sensible ML generates new features using internal factors like volume, revenue as well as external factors like weather and GDP.
Model Training and Deployment: Sensible ML automatically trains, tunes and deploys the best performing ML model.
Model Presentation: All model results and insights are tracked and presented to users however they choose within their normal OneStream planning processes.
Just like ML 123, Sensible ML is designed to enable finance teams to focus on collaborating with their business partners. This allows finance teams to leverage new insights to find new ways to ask why and extend their dialogue to make better decisions.
So what’s the best way to get started? Finance teams should consider advanced analytics as part of a broader framework that includes financial signaling, predictive analytics and ML.
Financial Signaling
Predictive Analytics
Unlimited Forecasting
Does your organization have data science resources?
YES
NO
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Goal-
Setting
Goal-
Setting
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MODELING
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MODELING
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PLANNING
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PLANNING
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operational
analysis
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Operational
analysis
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consolidate
& close
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consolidate
& close
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report &
analyze
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report &
analyze
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Figure 1
Here are a few uses cases for advanced analytics across
the Office of Finance:
R & D
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Executive Mgmt.
B.I. Competency Center
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Mktg.
& Sales
Finance
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YES, we use data science & machine learning today
We are CURRENTLY EVALUATING data science & machine learning software
We MAY USE data science & machine learning in the future
NO, we have no plans to use data science & machine learning at all
WEIGHTED MEAN
Figure 3
Finance
Executive
Mgmt.
I.T.
Mktg.
& Sales
B.I. Competency Center
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ADOPTION PLANS
WEIGHTED MEAN
Will Adopt BEYOND NEXT YEAR
Will Adopt NEXT YEAR
Will Adopt THIS YEAR
for Data Science & Machine Learning by Function
for Data Science & Machine Learning by Function
DEPLOYMENT PLANS
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REQUEST A DEMO
Copyright ©2020, OneStream Software, Inc. All rights reserved.
OneStream Software is a registered trademark of OneStream Software, Inc.
OneStreamSoftware.com
Sales@OneStreamSoftware.com
362 South Street
Rochester, MI 48307-2240
Phone: +1.248.650.1490
Contact Us
Companies that characterize themselves as data-driven and are in the top third
of their industry
are 5% more
productive and
6% more
profitable than
their competitors.
TOP
THIRD
Did You Know...
Finance
Executive
Mgmt.
I.T.
Mktg.
& Sales
B.I. Competency Center
4
3.5
3
2.5
2
1.5
1
0.5
0
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
for Data Science & Machine Learning by Function
ADOPTION PLANS
WEIGHTED MEAN
Will Adopt BEYOND NEXT YEAR
Will Adopt NEXT YEAR
Will Adopt THIS YEAR
Finance
Mktg.
& Sales
I.T.
B.I. Competency Center
Executive Mgmt.
R & D
4
3.5
3
2.5
2
1.5
1
0.5
0
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
for Data Science & Machine Learning by Function
DEPLOYMENT PLANS
WEIGHTED MEAN
NO, we have no plans to use data science & machine learning at all
We MAY USE data science & machine learning in the future
We are CURRENTLY EVALUATING data science & machine learning software
YES, we use data science & machine learning today
Copyright ©2020, OneStream Software, Inc. All rights reserved. OneStream Software is a registered trademark of OneStream Software, Inc.
OneStreamSoftware.com
Sales@OneStreamSoftware.com
362 South Street
Rochester, MI 48307-2240
Phone: +1.248.650.1490
Contact us