Modern Finance at Microsoft US
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Microsoft CFO, Americas, Jack Ryder shares the digital transformation of Microsoft US finance.
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Modern Finance at Microsoft US
- 2. Β© Copyright Microsoft Corporation. All rights reserved.
- 3. βBy adopting innovative technologies, finance will strengthen itβs business leadership through compliance, accuracy, and efficiency.β β Amy Hood, Executive Vice President and Chief Financial Officer, Microsoft
- 4. Β© Copyright Microsoft Corporation. All rights reserved.
- 5. Β© Copyright Microsoft Corporation. All rights reserved. 2000 2005 2010 2015 Today Power Pivot Power Query Power View One Finance Core Finance β βDiscipline at the core, flexibility at the edgeβ Microsoft Solutions β Accounts payable β Procurement β Standard reporting β Consistent taxonomies β Accounting transactions recording β Statutory & Tax β Business Process Automation β Risk Management Azure + Dynamics 365 + Microsoft 365 Modern Finance β βTransform using MS Cloudβ β Financial Analysis & Reporting β Strategy & Forecasting
- 6. Β© Copyright Microsoft Corporation. All rights reserved. Business Process Automation Risk Management Strategy & Forecasting Financial Analysis & Reporting
- 8. Β© Copyright Microsoft Corporation. All rights reserved. Financial Modern Business Management Portal Tax Analytics Platform Interactive Financial Statements External Financial Reporting Global Business Reviews on KPI Lake Customer Lifetime Value Analytics
- 9. Β© Copyright Microsoft Corporation. All rights reserved. Strategy & Forecasting Machine Learning Revenue Forecasting Machine Learning Accounts Receivable Forecasting Predicting Xbox Game Volume Real Estate Capacity Planning Headcount Forecasting Services COGS Forecasting
- 10. Β© Copyright Microsoft Corporation. All rights reserved. Business Process Automation Finance Operations Chatbot Credit & Collections Chatbot Contracts Setup Automation Financial Management Reporting Automation MSTravel AppTax Report Automation
- 11. Β© Copyright Microsoft Corporation. All rights reserved. Risk Management Global Policy Tool Compliance Predictive Analytics Blockchain SmartLink: Excel to Word Cross-linking in the Cloud General Data Protection Regulation (GDPR) Travel, Gift and Hosting Compliance
- 12. Β© Copyright Microsoft Corporation. All rights reserved. After Deep analytical and strategic thinking Operational thinking Transactional expertise Task management Basic business understanding Influencing and negotiating Diverse project management Advanced business knowledge Skillset Time spent on various activities in Finance
- 13. Β© Copyright Microsoft Corporation. All rights reserved. 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Finance Employees MSFT Revenue Since 2009 headcount has grown only 14% while revenue is up 89%
- 14. Β© Copyright Microsoft Corporation. All rights reserved.
- 15. Β© Copyright Microsoft Corporation. All rights reserved.
Editor's Notes
- When we talk to customer CFOs, here are some examples of the challenges they have and why they need Modern Finance These challenges look all old, but the reality is that a lot of our customers are still struggling with these challenges Some of these challenges are also part of our own Finance challenges in Microsoft: Several of our Customers are still living with Legacy Systems created 20 years ago (In MS: BWB still around) Using Static Reports and not able to drill down to find insights (In MS: Old MYR Decks) Data is the new Strategic Asset for CFOs. The amount of data is doubling every year in the World and several of our customers have not yet created their βsingle source of the truthβ Business is becoming more complex every day, having old tools that were built for old business models is not helpful (In MS: New Business in MSS) Several Finance Processes that our customers do are still manual. Sometimes the people managing these processes are great on what they do but subject to human error (In MS: Closing, Reconciliations) Finally, as the world grows, there are new business risks and threats, there is a need for more regulations. We just canβt rely on manual processes, we need to develop our tools to proactively help us mitigate risks. (In MS: Old way to sample deals for Compliance Review)
- Obtain a relevant quote relating to Finance Showcase
- As Microsoft has evolved over the last 30+ years, so has the finance function. The first two decades of Microsoft Finance were defined by a centralized system focusing primarily on controllership and the fundamentals, an appropriate approach for a fast growing and relatively smaller company. Around 2002, we decentralized the finance function, moving finance roles into our growing business groups and appointing new divisional CFOs. We also started to go deeper in our finance operations such as forecasting, asking field teams to share their outlook in much more detailβby product, by sales type, and by customer segments. Everything we did was manual and adhoc, primarily using Excel and other Office tools. We set of on a journey in 2005 to standardize what we do and increase internal controls so we can really say we know what we have in our books and Measure what we do.β We launched an initiative called OneFinance to centralize some processes into three regional operating centers and outsource transactional work in Accounts Payableβ, Procurement (Buy Centre)β, Accountingβ and specifically tackle the stat & tax area Following that work and to address new business realities, in FY08 we embarked on a journey called COREFinance, summarized as βDiscipline at the core and flexibility on the edgesβ. The objective: to enable flexible reporting at all levels of the business while still explicitly adhering to corporate standards. COREFinance allows us to create one highly secure version of the truth pulled from multiple sources, and then turn that information into actionable insights across the enterprise with role-based security across it all.Β β Using Microsoft SQL Server to apply role-based security and business rules to a common data warehouse, we have democratized corporate data and created a one stop shop experience for all users. Our single portal experience enables centralization and standardization. With standard scorecards, reports, and analytics at the core, and added flexibility to drill down and apply analytics for self service, weβve created alignment and a culture of shared accountability. This standardization has been extended to include Microsoft Dynamics AX in some of our divisions to add agility, while we continue to run SAP as the core finance application. This enables greater business agility and transparency across our organization and empowers intelligent decision making.β Now, in the last few years weβve seen rapid advancement of our technology and have been ushering in greater digital transformation than ever before. We call this work Modern Finance
- Letβs talk now about the Digital transformation journey [CLICK] The journey is about taking DATA and turning into ACTION, adding VALUE to the Business in the fastest and most relevant way. But before we could do that, we had to work on preparing the DATA, cleaning up data, creating consistent taxonomies, moving it to the cloud, and creating the βsingle source of truthβ. Many of our Customers are still in this phase. [CLICK] Once DATA is clean and available we can now produce BUSINESS INTELLIGENCE. In the beginning we started with STATIC REPORTS, that could only tell WHAT HAPPENED. They didnβt allow the drill down capability and didnβt produce insights for our Business. Furthermore, the amount of MANUAL PROCESSES and work that we had to put together to build these reports and then produce insights was huge POWER BI came few years later, allowing interactive reporting, making meetings much more dynamic, helping us understand WHY IT HAPPENED, reducing the amount of Manual Processes, but still we could only look at the past and didnβt have the tools to help predict the future. [CLICK] Then we crossed the line and start looking at the future with ADVANCED ANALYTICS. With MACHINE LEARNING we can now learn from the past to predict the future, we can know WHAT WILL HAPPEN. The distance between DATA and ACTION is shorter now, the amount of MANUAL PROCESSES and human errors is lower now. Customers love this! Finally with a combination of MACHINE LEARNING + BOTS we get to the position that we can say WHAT TO DO, automating the decision making process and moving really fast from DATA to DECISION.
- Letβs talk now about the Digital transformation journey [CLICK] The journey is about taking DATA and turning into ACTION, adding VALUE to the Business in the fastest and most relevant way. But before we could do that, we had to work on preparing the DATA, cleaning up data, creating consistent taxonomies, moving it to the cloud, and creating the βsingle source of truthβ. Many of our Customers are still in this phase. [CLICK] Once DATA is clean and available we can now produce BUSINESS INTELLIGENCE. In the beginning we started with STATIC REPORTS, that could only tell WHAT HAPPENED. They didnβt allow the drill down capability and didnβt produce insights for our Business. Furthermore, the amount of MANUAL PROCESSES and work that we had to put together to build these reports and then produce insights was huge POWER BI came few years later, allowing interactive reporting, making meetings much more dynamic, helping us understand WHY IT HAPPENED, reducing the amount of Manual Processes, but still we could only look at the past and didnβt have the tools to help predict the future. [CLICK] Then we crossed the line and start looking at the future with ADVANCED ANALYTICS. With MACHINE LEARNING we can now learn from the past to predict the future, we can know WHAT WILL HAPPEN. The distance between DATA and ACTION is shorter now, the amount of MANUAL PROCESSES and human errors is lower now. Customers love this! Finally with a combination of MACHINE LEARNING + BOTS we get to the position that we can say WHAT TO DO, automating the decision making process and moving really fast from DATA to DECISION.
- Letβs talk now about the Digital transformation journey [CLICK] The journey is about taking DATA and turning into ACTION, adding VALUE to the Business in the fastest and most relevant way. But before we could do that, we had to work on preparing the DATA, cleaning up data, creating consistent taxonomies, moving it to the cloud, and creating the βsingle source of truthβ. Many of our Customers are still in this phase. [CLICK] Once DATA is clean and available we can now produce BUSINESS INTELLIGENCE. In the beginning we started with STATIC REPORTS, that could only tell WHAT HAPPENED. They didnβt allow the drill down capability and didnβt produce insights for our Business. Furthermore, the amount of MANUAL PROCESSES and work that we had to put together to build these reports and then produce insights was huge POWER BI came few years later, allowing interactive reporting, making meetings much more dynamic, helping us understand WHY IT HAPPENED, reducing the amount of Manual Processes, but still we could only look at the past and didnβt have the tools to help predict the future. [CLICK] Then we crossed the line and start looking at the future with ADVANCED ANALYTICS. With MACHINE LEARNING we can now learn from the past to predict the future, we can know WHAT WILL HAPPEN. The distance between DATA and ACTION is shorter now, the amount of MANUAL PROCESSES and human errors is lower now. Customers love this! Finally with a combination of MACHINE LEARNING + BOTS we get to the position that we can say WHAT TO DO, automating the decision making process and moving really fast from DATA to DECISION.
- Letβs talk now about the Digital transformation journey [CLICK] The journey is about taking DATA and turning into ACTION, adding VALUE to the Business in the fastest and most relevant way. But before we could do that, we had to work on preparing the DATA, cleaning up data, creating consistent taxonomies, moving it to the cloud, and creating the βsingle source of truthβ. Many of our Customers are still in this phase. [CLICK] Once DATA is clean and available we can now produce BUSINESS INTELLIGENCE. In the beginning we started with STATIC REPORTS, that could only tell WHAT HAPPENED. They didnβt allow the drill down capability and didnβt produce insights for our Business. Furthermore, the amount of MANUAL PROCESSES and work that we had to put together to build these reports and then produce insights was huge POWER BI came few years later, allowing interactive reporting, making meetings much more dynamic, helping us understand WHY IT HAPPENED, reducing the amount of Manual Processes, but still we could only look at the past and didnβt have the tools to help predict the future. [CLICK] Then we crossed the line and start looking at the future with ADVANCED ANALYTICS. With MACHINE LEARNING we can now learn from the past to predict the future, we can know WHAT WILL HAPPEN. The distance between DATA and ACTION is shorter now, the amount of MANUAL PROCESSES and human errors is lower now. Customers love this! Finally with a combination of MACHINE LEARNING + BOTS we get to the position that we can say WHAT TO DO, automating the decision making process and moving really fast from DATA to DECISION.
- Letβs talk now about the Digital transformation journey [CLICK] The journey is about taking DATA and turning into ACTION, adding VALUE to the Business in the fastest and most relevant way. But before we could do that, we had to work on preparing the DATA, cleaning up data, creating consistent taxonomies, moving it to the cloud, and creating the βsingle source of truthβ. Many of our Customers are still in this phase. [CLICK] Once DATA is clean and available we can now produce BUSINESS INTELLIGENCE. In the beginning we started with STATIC REPORTS, that could only tell WHAT HAPPENED. They didnβt allow the drill down capability and didnβt produce insights for our Business. Furthermore, the amount of MANUAL PROCESSES and work that we had to put together to build these reports and then produce insights was huge POWER BI came few years later, allowing interactive reporting, making meetings much more dynamic, helping us understand WHY IT HAPPENED, reducing the amount of Manual Processes, but still we could only look at the past and didnβt have the tools to help predict the future. [CLICK] Then we crossed the line and start looking at the future with ADVANCED ANALYTICS. With MACHINE LEARNING we can now learn from the past to predict the future, we can know WHAT WILL HAPPEN. The distance between DATA and ACTION is shorter now, the amount of MANUAL PROCESSES and human errors is lower now. Customers love this! Finally with a combination of MACHINE LEARNING + BOTS we get to the position that we can say WHAT TO DO, automating the decision making process and moving really fast from DATA to DECISION.
- Flat Finance OPEX post-Financial Crisisβ β Finance headcount flat while business grew in revenue and complexityβ β Increase usage of standard tools and technology helped to drive productivity gainsβ
- You donβt have to pick everything β get some comfort level in your organization. Build confidence. Picking key area and making progress is a great start. Will also point out core challenges you have β such as data β it was the first square on my slide. You have a lot of it. It needs to be searchable and structured and consistent. Be careful about the team you pick β pick those more comfortable with technology and more willing to go on that journey. Once others see they are successful they will take the same journey Grow capabilities Listen a few years ago I'm not sure we had the same level of expertise we had that we have no in fiancΓ©. We partnered deeply with our CIO and its about a partnership to go on this journey. This goes hand-in-hand. Finally, get started.