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1、Crunch time seriesIts time to get serious about dataIs data a challenge for your finance organization?If you answer yes then what?0102030405060CostmanagementFinancial performanceGrowth(organic and inorganic)Capital allocationTalent/laborTransformation(i.e.,business model,enterprise,finance)Strategy

2、setting and executionSupplychainITinfrastructureRegulatoryreadinessData analytics/AI/businessintelligenceProcess andoperations37%23%23%22%15%14%12%8%52%50%38%10%2As CFO,what are your top three priorities for 2023?Deloitte,CFO Signals:4Q 2022,2022.Survey included 126 CFOs from the United States,Canad

3、a,and Mexico.3It almost seems fundamental:Of course,data is vitally important,and no Finance leader would say different.That is,until you ask about other priorities.Theres cost management and financial performance,of course.Growth.Talent.Compliance.And on down the list.Each of these concerns claims

4、its share of a CFOs time and attention until finally we get towhat were we asking about again?Right:data.Now ask a new question:Which of those other priorities can you expect to master if you dont have data completely under control?Not one of them.So,no matter what people practice or preach,data rea

5、lly is central.The real question is whether you treat it that way.Its time to get serious about data.Data is a top priority for our finance team.Except forEverywhere a CFO turns,something underscores the need to care about and prioritize data:compliance with new regulations and demands for transpare

6、ncy,supporting agile and effective decision-making amid rapid change,and reacting to market and stakeholder demands as business cycles continue to shorten.Data is central even to the hiring and upskilling that keeps a finance organization on its toesand in hiring and retaining talent with data skill

7、s,the competition includes not only finance but the whole business world.When Finance treats data as a first-tier priority,it can excel across more than one dimension.Not in spite of other pressures,but because of them4Data availability:Information on demand,where and when its needed.Data completene

8、ss:Telling the whole story at every touchpoint.Data detail:Information thats granular enough to drive sound,timely decisions.Data standardization:Consistent formats and standards regardless of source or use.Data accuracy and credibility:Not only accurate data,but relevant,timely information that sta

9、keholders agree is meaningful.The common thread in these imperatives is the need to turn data you have into information you can use.A comprehensive approach like this can elevate Finance to a more strategic role within the organization.Achieving these aims will require a focused effort with leadersh

10、ip commitment to see and manage the big data picture.5Some organizations are not aware of the full range of stakeholders who use data.Thats why its foundational to understand in specific terms where Finance data originates and who consumes it.Lets be clear what kind of data were talking about.What k

11、inds of data does Finance use?Where does it come from?Where is it used,by whom,and for what purpose?Financial systemsHR systems ERP Data warehouses Planning systems Consolidation tools Reporting tools Tax systems Treasury systems Intelligent automation Spreadsheets/shared filesWhere Finance data can

12、 originateWhat data Finance can useWhere,how,and by whom Finance data can be consumedFinancial actualsRegulatory reporting bodiesInvestorsCreditorsAnalystsManagementOperationsEmployeesCustomers Local GAAP IFRS Global stat Managerial TaxForecasting Local GAAP Managerial TaxOperational Transactions HR

13、 Commercial Supply chainSupply chain and procurement systemsVendors/suppliersBoards of DirectorsCommercial systems IT systems Vendor/alliance systemsMarket data(internal and external)Economic indicatorsReal estate systems6The trajectory of Finance data Each organization is different,but a clear unde

14、rstanding of the trajectory of your Finance data can help you better harness its power.7Whats insideConsider all data important 8Focus only on financial data 10Dont have a formalized finance data organization 12The big picture20The path ahead210107080203040506Dont have Finance roles and career paths

15、 for“data people”14Spend most of the time in spreadsheets 16Arent thinking about automating data 18Time to put priorities to the testWhat does“getting serious about data”look likeespecially if you believe you already are?Ask yourself whether you:8The first priority is not to prioritize.When in doubt

16、,capture as much as you can;then sort and refine it later.Right?Not so fastor,rather,not so much.Collecting all the data you can at the lowest level of detail can set you up for headaches and bottlenecks later.The more intake you haveespecially if it arrives in different formats from different sourc

17、es with no standardization around key attributes,such as profit centers,cost centers,general ledger accounts,customers,and productsthe more effort and bandwidth it takes to load into downstream systems with proper governance and attribution.Inconsistent definitions,or the use of a broader array of m

18、anagement dimensions such as product,customer,geography,channel,or line of business,can also add confusion.Similar problems can arise if you focus too much on the presentbecause“present”can be another word for“temporary”as business needs for information and insights evolve over time and new data dom

19、ains,ESG being a top-of-mind example,may be needed in the future.Ultimately,failure to invest in thoughtful data prioritization upfront can limit the efficiency benefits of major core technology investmentsfrom ERPs to data warehouses.03020607050401030208Its time to get serious about data ifYou cons

20、ider all data importantInconsistent definitions,or the use of a broader array of management dimensions such as product,customer,geography,channel,or line of business,can also add confusion.9Moving targets,mounting confusionHigh-growth companies sometimes expand from a single-product focus to multi-p

21、roduct,multi-channel operations.That can be a boon for growthbut,initially,a setback for data alignment.Their existing enterprise resource planning(ERP)platforms may not be designed to handle that business model shift.So,when it happens,they have to enrich large amounts of data offline or outside th

22、eir core platforms.Reporting can become tangled,and planning,forecasting,and analytics capabilities suddenly become much less effective because they dont match a shift in business with a corresponding change that would keep critical decision-making information flowing as needed.The truth is not all

23、data is equal in importance.But it should be equal in usability.It should serve an identified needsuch as financial,operational,sustainability,or whatever you valuebased on your industry and operations.In addition,a forward-thinking approach to data standards can help maintain alignment across exist

24、ing systems,future ones,and ones you may acquire through integration.Applying these principles wont always be easy.They can introduce transition and rebuild costs,especially in more complex organizations.If you acquire another company,you may have a lot of existing structures to untangle and adapt.B

25、ut todays work to standardize,prioritize,and anticipate the future can pay off down the road.Define what data,at what level of detail,can help you understand the value drivers of your business and support decision-making aligned with your business strategy and performance management,help you underst

26、and and run your business,and help to motivate and inform your leadership.Establish a data model and curated data sets that provide a standardized way of capturing and reviewing data aligned to the different ways the data will be used.Create and use common standards and data tiers that harmonize dat

27、a from different sources,determine what data matters,and dictate how to cleanse and prepare it.Align your data to a realistic view of which downstream processes it is meant to inform.Adopt robust governance that can meet continually changing data needs in areas such as capturing,storing,securing,con

28、trolling,and reportingas well as scenarios like divestiture or management structure change.Match requests for information to the performance management expectations that data is meant to supportno more,no less.03020607050401030208What serious looks like1003020607050401030208If youre in Finance and f

29、ocus closely on the sources of your data,youre likely to look close to homein Finance.But you need to think bigger.Todays Finance organizations handle management reporting that requires sources from supply chain,marketing,HR,and external data.In addition,the outputs of your work help drive enterpris

30、e-wide decision-making linking tax,statutory accounting,and financial planning to forecasts and models spanning commercial,supply chain,operations,talent,and beyond.If different data streams dont alignfor example,if supply chain and Finance define and use cost centers differentlyit can get cumbersom

31、e to turn knowledge into insight.Its time to get serious about data ifYou focus only on financial dataIf different data streams dont alignfor example,if supply chain and Finance define and use cost centers differentlyit can get cumbersome to turn knowledge into insight.11Looking beyond Finance doesn

32、t mean overlooking Finance.Casting a more comprehensive net can help your team perform more accurately and effectively as accounting and performance management goes from periodic to real time.A broad view may help you build forecasting and predictive capabilities that help turn your Finance assembly

33、 line into a Finance engine.Identify operational data that can work alongside financial data to help inform management decisions.Plan for tax,statutory accounting,and other functions from the start,not as an afterthought.Present financial results in context with proactive inclusion of relevant dataf

34、or example,you might have taken a loss,but it was less than your competitors.Integrate and coordinate data from systems outside Finance.Align from the beginning on how data originates from vendors,customer orders,SKUs,and similar sources with the appropriate attributions.Establish clear and tailored

35、 controls based on the type,source,and usage of data.Develop accountability standards for the use of operational and third-party data.Look further afield for newly relevant sources(like ESG,DEI,and sustainability data)that affect your organization.What serious looks like0302060705040103020812Data is

36、 a shared asset but not a shared responsibility.Formalized ownership of data standards and data quality is key to effectively managing data,and without ownership and governance,it will likely remain difficult to harness its power.And data ownership and process ownership are not the same thing.That d

37、oesnt mean its time to appoint a single person or role and walk away.Different constituents for the data finance uses will have different requirements,sometimes transformational ones.The team that oversees data should be able to name all the stakeholders that consume it and know the sources of truth

38、 they use.They need to work across the organization to elevate the implications of poor data visibility and not allow finance to default to temporary fixes that allow finance processes to continue for now,but not deal with the underlying data issues.Conversely,the people outside the data team who co

39、nsume information should understand the processes that create and deliver their data;without this data literacy training,they may not fully understand the ways their actions affect the data(and vice versa).This is ultimately the CFOs responsibility,but just like so many other things that fit that de

40、scription,the solution may lie in delegating governance to a dedicated team.Its time to get serious about data ifYou dont have a formalized Finance data organizationDifferent constituents for the data finance uses will have different requirements,sometimes transformational ones.030206070504010302081

41、3Leading organizations establish Finance data functions with defined,clearly assigned responsibilities that span data standards definition and documentation,data process design,and execution,and they distinguish between teams that set the rules for data governance and teams that execute requests for

42、 data creation.Every data management team for Finance should have clear lines of accountability and a specifically determined scale,focus,and funding mechanism,all under the direct oversight of the CFO,linked to a broader enterprise data governance approach that allows them to engage across function

43、s and stakeholders.Establish the business case,identify innovative and feasible funding mechanisms to help formalize and transform the organization.Develop a culture of accountability around data that has policies and procedures regarding roles and responsibilities,as well as goals and objectives ti

44、ed to performance.Define a clear governance structure with data stewards accountable for specific data sets.Stewards engage cross-functionally and with IT to understand requirements but are empowered to make data related decisions.Govern data at the rate you create it.Tie data decisions back to busi

45、ness reasons.Shift your mindset from cleaning up data one time to an ongoing approach that creates,cleanses,and maintains data in pace with the business.Build adequate tools and a technology infrastructure to store,process,analyze,and report on data.What serious looks like0302060705040103020814If th

46、e career path you offer data professionals in your Finance organization is one-size fits all,then youre not serious about data.Similarly,if you have Finance employees who feel their job titles make them“non-data”people,you need to do more.The ability to access and use data is something you should em

47、bed throughout the organization building data competency that allows every finance employee to be able to spot opportunities to use analytics and derive insights.What are you doing to make your shop an attractive place for the most capable people?What are you offering to existing team members to hel

48、p them add and refine data related skills?Most importantly,is there a recognizable path forward for people in that specialty?Its time to get serious about data ifYou dont have finance roles and career paths for data peopleWhat are you offering to existing team members to help them add and refine dat

49、a-related skills?0302060705040103020815Priming the talent pipelineAs in other areas,Accounting and Finance are traditionally viewed as late adopters of these data practices.Perhaps your organization needs help accelerating its own data talent pipeline.Fortunately,a new focus in higher education is p

50、reparing students for careers in data,specifically as it relates to the finance industry.If data is central to your performance as a Finance organization,the ways you bring talent to bear on it shouldnt be left to chance.When you compete for Finance talent,youre likely only competing against your pe

51、ers in the same discipline.When you compete for data talent,youre competing with employers in every field.Start by knowing what business problems your data needs to address and how this can inform your talent needs and data competency development approaches.Establish several multi-disciplinary caree

52、r paths that align data capabilities with specific functions within the Finance organization.Turn to influencers from across the organization to help enhance internal finance data capabilities including supporting upskilling and knowledge sharing.Prepare to adapt roles based on industry changes,such

53、 as ESG reporting.Develop a specific talent acquisition and retention plan for data people that offers competitive compensation,benefits,impact,mentorship,and trainings,etc.What serious looks like0302060705040103020816Data is a resource.The value you derive from it is certainly a resource.And presum

54、ably,youre an enterprise.So why is your financial data and its output not wired into an ERP platform and enterprise performance management(EPM)and reporting systems?Finance teams turn to spreadsheets for analysis when they need to align and curate data from different systemsmeaning no standardized s

55、ystem has applied common data standards beforehand.Its also common to see spreadsheet use in cases when an organization has not aligned its data,has not aligned its performance management practices,or carves out special views for executives.If your teams bring you reports in spreadsheets and slide d

56、ecks,you are not leveraging the performance management and data visualization technologies that are designed to integrate with your ERP and manage your processes and improve them over time.The old ways may be familiar,and your teams may be skilled in using them as workarounds,but thats still what th

57、ey are.Getting better at doing things the old way doesnt fix the problem in the long run.Its time to get serious about data ifYour team is spending more than half of their time in spreadsheetsGetting better at doing things the old way doesnt fix the problem in the long run.0302060705040103020817An e

58、fficient organization should centralize,standardize,and validate information,making it available in one place,to create a golden source of truth.Accomplishing this can spell the difference between a merely efficient organization and an insight-driven one.The finance organization should be at the hea

59、rt of that,not an outlier.That means sourcing,curating,and using data in ways that support not only traditional reporting but leading-edge functions,such as predictive analytics and machine learning.Your ERP likely cost tens of millions,if not more.It ought to be adding its value to your reports and

60、 insights if it isnt already.Be patient and fix issues with your technology enablement over time.Pursue ERP integration one process at a time instead of all at once,and prioritize.Interrogate the ways ERP integration can deliver more timely and useful insights,and work backward from business needs.P

61、rioritize data availability in decisions about sourcing,formatting,and hosting.Keep your core ERP clean,with a common set of processes for each enterprise if feasible,and have a clear plan of what data is housed in your periphery systems(e.g.,EPM,reporting).What serious looks like0302060705040103020

62、818More.Faster.Richer.We all know data is growing in every way we can measure it.How long can“throw more bodies at it”remain a sustainable response?Beyond a certain threshold,keeping up with scale means turning to automation.And youve probably already passed it.It might be a generalization to say Fi

63、nance organizations tend not to adopt new technology as quickly as other parts of an enterprise do,but whether thats true across industries,it shouldnt be true in your organization.Building automation capabilities into the ways you create,regulate,store,and use data has the potential to carry you pa

64、st the limits of human governance and unlock more performance.Because the volume of data and the ways in which its used continue to grow,automation is also increasingly the key to maintaining the necessary availability of data.Its also true that“more”doesnt translate to“better”in a strictly linear w

65、ay:There is a trade-off between how rich your data is and how efficiently Finance organizations can operate in transaction processing and closing the books.Its time to get serious about data ifYou arent thinking about automating dataBecause the volume of data and the ways in which its used continue

66、to grow,automation is also increasingly the key to maintaining the necessary availability of data.0302060705040103020819All of this requires detailed knowledge of what youre working withdetail in the data itself,sufficient standardization,and verified sourcing and quality.As your organization grows,

67、its vital to maintain clarity on who owns the data and how you use it to make decisions.That will likely involve representation from areas outside Finance,particularly if another business is acquired.At the highest level,“serious”starts with an embrace of automating Finance data and its use.Manageme

68、nt and financial reporting simply depend on that capability today.Beyond that,there are several ways to drill down:Establish clear controls and rules that enforce checks on data at the point of creation.Enable self-healing data supported by Machine Learning(ML)-driven data quality standards.Invest i

69、n self-corrective and self-healing technologies to manage master data coherently through AI/ML-powered chatbot-based workflows and assets that can evolve with your data needs.Empower humans to work with machines with a focus on exceptions that require human intervention and context.Develop reconcili

70、ation and controls to improve and continuously maintain data quality.What serious looks likeAutomating supplier master dataSupplier data streams and operational steps are increasing due to higher vendor counts and reporting or data requirements.Todays processes are managed over communications,email,

71、and manual recollections and data entry,frequently with low levels of data governance.Data stewards spend their time absorbed in manual retracing and entry of data.Imagine instead a business data steward who can access one true supplier master dataset across the enterprise.Reference templates and da

72、ta are readily available,minimizing manual data entry.The steward can now validate data in real time across business and regional units and provide recommendations to optimize enterprise outcome.Solving data gaps becomes a function of the past,as ML connects the dots for commonalities across the bus

73、iness.0302060705040103020820There are a lot of insights in these pages,and it would be easy to take on too much too fast.The idea is to evolve the use of data in your Finance organization,and not to be more disruptive than is necessary.So dont try to tackle everything all at once.As always,address n

74、eeds before process:Start with the business problem youre trying to solve.That can lead you to the quick wins and easy early steps and avoid analysis paralysis that all data must be fixed or perfect.Addressing those needs wont just deliver faster returns but also will help you clarify roles,responsi

75、bilities,and your vision for Finance data in a way that will set up a smoother experience on later,bigger projects.The big picture0302060705040103020821Data is an asset.Acquiring it and managing it carries costs.You should expect a return on that investmentand no investment produces a return if you

76、take it for granted.From sourcing to cleansing to governance,often across multiple legacy systems,data is a resource you need to take control of and put to work.From the top down,your finance organization should have a North Star data strategy.Where do you want to go?How can you get there?What benef

77、its can you realizenot just in cost savings,but in new capabilities to strategically collaborate with the business?A clear strategy is a necessary bedrock for defining roles and responsibilities,determining priority levels,and establishing accountability.For many organizations,becoming an effective

78、data-driven organization is easier when Finance has a place at the strategic table in addition to its functional role.The person in this role,whatever their title,governs the data lake and is the custodian of the companys data management policy.Whatever title comes with this job,it needs to be occup

79、ied by someone who understands the ways data drives business and customer value.This role can help organizations increase their understanding of data,link it to business outcomes,and improve efficiencies.If you dont make those connections,no matter how much data you have,its just data for datas sake

80、.The path ahead0302060705040103020822Its Crunch time.There was a time when keeping on top of your manual entries meant you were on top of your Finance information.Then you switched to local spreadsheets.Then you started sharing them on a server or the cloud.Evolution in Finance data isnt new;its jus

81、t at a turning point.Getting serious about data is no longer an incremental need for Finance.Its a transformative oneor a reason transformation might fail.Data is raw material,and it doesnt turn into information,insight,plans,or decisions until its managed and interpreted.Doing that at human scale i

82、s simply not feasible today.For many Finance organizations,data is an area in which they have to play catch-up.But that just means they have more opportunity waiting to be seized.The good news is there are more tools than ever to help carry that process forward.It wont be easy.But then if the way yo

83、u approach finance data isnt hard,youre not serious about data.The work is there.The benefits are clear.Time to get started.Getting serious about data is no longer an incremental need for Finance.Its a transformative oneor a reason transformation might fail.0302060705040103020823AcknowledgmentsAutho

84、rsKirti Parakh Managing Director,Audit and Assurance,Accounting,Advisory&Transformation ServicesDeloitte&Touche LLP Tel:+1 312 486 3937Email:Dave PierceManaging Director,Consulting,Finance and Enterprise Performance Deloitte Consulting Tel:+1 703 251 4088Email:Putri Sukardi Managing Director,Risk an

85、d Financial Advisory,ControllershipDeloitte&Touche LLPTel:+1 513 723 3063Email:Srikanth TammaManaging Director,Consulting,Enterprise Technology and Performance Deloitte ConsultingTel:+1 214 840 7992Email:Marla McPheetersSenior Manager,Consulting,Strategy and AnalyticsDeloitte ConsultingTel:+1 312 48

86、6 5387Email: ContributorsSusan HoganRenee AnningaPankaj ArjunwadkarBenjamin BarudinLucy ChungMike DanitzVjola DulePriya EhrbarAla El-KourJonathan EnglertEldy FalixMartin HodgettsEric MerrillRyan McWhorterRanjit RaoThomas RavnRyan ReiberJeevi ParamanathanPhilippe PodhoreckiDaniele SacerdotiJoAnna Scu

87、llinRichard SideyAdrian TaySimo UusijokiJamie Weidner0302060705040103020824Susan HoganPrincipal,Finance Transformation Practice LeaderDeloitte Consulting LLPTel:+1 404 631 2166Email:Jonathan EnglertPrincipal,Finance Transformation Eminence LeadDeloitte Consulting LLPTel:+1 215 405 7765Email:Diane Ma

88、Principal,Consulting,Finance&Enterprise PerformanceDeloitte Consulting LLPTel:+1 213 553 1221Email:Jessica BierManaging Director,Consulting,Human CapitalDeloitte Consulting LLPTel:+1 415 783 5863Email:Jonathan PearcePrincipal,Consulting,Human CapitalDeloitte Consulting LLPTel:+1 646 301 1407Email:Va

89、run DhirPrincipal,Consulting,OracleDeloitte Consulting LLPTel:+1 484 868 2299Email:Eric BramleyManaging Director,Consulting,SAPDeloitte Consulting LLPTel:+1 404 631 2145Email:Dan SiegelPrincipal,Consulting,Emerging ERP SolutionsDeloitte Consulting LLPTel:+1 973 602 5411Email:Clint CarlinPartner,Risk

90、 and Financial Advisory,ControllershipDeloitte&Touche LLPTel:+1 713 504 0352Email:Sarah FedelePrincipal,Risk and Financial Advisory,Internal AuditDeloitte&Touche LLPTel:+1 713 982 3210Email:Mike KosonogPartner,Risk and Financial Advisory,CyberDeloitte&Touche LLPTel:+1 313 919 3622Email:Prashant Patr

91、iPrincipal,Risk and Financial Advisory,TreasuryDeloitte&Touche LLPTel:+1 212 436 7568Email:Scott Shafer Principal,Tax,Tax Technology Consulting Deloitte Tax LLP Tel:+1 312 486 5340 Email:Ed NevinPartner,Tax,Tax SpecialtyDeloitte Tax LLPTel:+1 410 576 7359Email:Scott SzalonyPartner,Audit and Assuranc

92、eDeloitte&Touche LLPTel:+1 248 345 7963Email:Steve GallucciPartner,CFO Program LeaderDeloitte&Touche LLPTel:+1 212 436 5914Email:Jeff GoodwinPartner,Risk and Financial Advisory,Government&Public ServiceDeloitte&Touche LLPTel:+1 303 921 3719Email:Christie JohnsonPrincipal,Consulting,Government&Public

93、 ServiceDeloitte Consulting LLPTel:+1 571 814 7571Email:Contacts03020607050401030208To find out more,please visit DeloitteDeloitte refers to one or more of Deloitte Touche Tohmatsu Limited,a UK private company limited by guarantee(“DTTL”),its network of member firms,and their related entities.DTTL a

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