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Essential Guide to AnalyticProcess Automation (APA)The convergence of Analytics, Data Science, and Process Automation

CONTENTSDigital Transformation3Data Process People4The Catalyst for Transformation8The Proven Analytic Process Automation Platform11Four Areas of Realized ROI14What You Can Expect15The Power of the Alteryx Community162

E S S E N T I A L G U I D E T O A N A LY T I C P R O C E S S A U T O M AT I O N ( A PA )Digital TransformationWhat Drives SuccessIn a recent McKinsey global surveyon digital transformation1, eight outof every 10 respondents said theirorganizations have embarked on a digitaltransformation journey in the last fiveyears. That’s promising news. However,only one third of these initiatives havesucceeded. For such organizations thedigital transformation journey remainselusive. What stands out amongst thosethat failed is a common theme; theseorganizations embarked on their digitaltransformation journey with a tendencytowards looking inward when evaluatingtheir people, processes, data, andtechnologies. Those organizations thatgreatly succeeded looked outside. Theyrecognized the value of new automationand transformation technologies and theychose to deliberately invest in technologysupported change.Results from these successful digitaltransformations show that theseorganizations selected technology andpractices that converged three criticalkey pillars of digital transformationspecifically, the democratization ofdata analytics and data science, theoptimization and automation of businessprocesses, and the upskilling of people.This converged approach to digitaltransformation is consistently yieldinghigher rates of success.The proliferation of augmented capabilitieswithin analytics, business intelligence, anddata science and machine learning productsis making once-distinct markets collide.The collision facilitates stronger, morecomplete and more effective links betweendata and analytic investments, practices,processes and key business outcomes."Gartner, Worlds Collide as Augmented Analytics Draws Analytics,BI and Data Science Together, Carlie Idoine, 10 March 20201McKinsey, Unlocking Success in Digital Transformations3

E S S E N T I A L G U I D E T O A N A LY T I C P R O C E S SAUTOMATION (APA)Data Process PeopleA Converged ApproachIt is now a strategic imperative to both capitalizeon the data economy and accelerate digitaltransformation. Successful execution requireselevating data assets, analytics, daily businessprocesses, and people towards business goalsand outcomes. People, processes, and data are anorganization’s richest assets, and when these threeassets are addressed together, transformativeoutcomes are realized.A unified technology platform that provides accessto requisite and relevant data while automatingbusiness processes and fostering the rapidupskilling of people within an organization isrequired to drive success for digital transformationinitiatives. These platforms provide comprehensiveautomation capabilities across the continuumof diverse data access, diagnostic, predictive,prescriptive analytics, augmented AI and machinelearning, and business process automation. Mostimportantly, they foster deep engagement of theworkforce to enable the rapid upskilling of people.Digital transformation success is elusive when organizations failto converge the three pillars that accelerate analytics outcomes:Data, Processes, and People.4

E S S E N T I A L G U I D E T O A N A LY T I C P R O C E S SAUTOMATION (APA)Democratizing Data and AnalyticsThe first priority in embarking on digitaltransformation is to make information moreaccessible to everyone across the organization.55% of organizations agree that data analytics fordecision-making is extremely important today,and 92% confirm the increasing importance ofdata and analytics through 2020 and 2021¹. Thishas driven organizations to do away with outdatedtools and adopt modern self-service analytics anddata science solutions.Today’s integrated self-service analytics anddata science solutions have proven to simplifyand broaden the accessibility of data, analytics,and data science to everyone without needingspecialized skillsets and even apply AI andmachine learning without having to be an expertor coder. They enable advanced diagnostic,predictive, and prescriptive analytics, machinelearning, and AI via a simple self-service experiencethat engages the workforce and acceleratesachieving a culture of analytics.Optimizing and AutomatingProcessesAn equally critical pillar of successful digitaltransformation is the optimization and automationof both tedious and complex processes usingsmarter technologies. Early digital transformationfailures simply took existing processes andmirrored them into preexisting technologies.Successful digital transformation, however, firstevaluates existing processes, modifies processesand procedures with a focus on achieving fasterbusiness outcomes, and applies technology tooptimize and automate processes to deliverintelligent business process automation. In allcases, this has proven to speed critical businessprocesses and achieve far greater efficiencies andbusiness outcomes.570%of an analyst’s timeis spent searchingfor data; 44% of dataworkers’ time resultsin unsuccessfulattempts.IDC, State of Data Science and Analytics99.4%EFFICIENCYA large nationalretailer automatedparcel routing anddeliveries resultingin 99.4% on-timedeliveries and 11% incost savings.

E S S E N T I A L G U I D E T O A N A LY T I C P R O C E S SAUTOMATION (APA)4,000 UPSKILLEDA top 10 automotivecompany upskilled4,000 people acrossmultiple lines ofbusiness.The Perpetual Upskilling of PeopleWhen it comes to reskilling and upskilling theworkforce, successful digital transformationrequires shifting people’s focus from forcedlearning to development of outcome-focusedmindsets and capabilities. They start with the endin mind. Outcome-focused mindsets are developedby letting people explore humancentered, selfservice technologies and experience the thrill ofcreating new outcomes for the business.DATADemocratizingdata and gpeopleUnified software platforms provide data analytics, data science,and process automation capabilities across the entire digitaltransformation capability continuum and bring togetherbusiness users, citizen analysts, and information consumers toaccelerate organization-wide outcomes.The sharing of their individual outcomes thenamplifies the collective intelligence of a workforcewho then aspire to achieve even bigger wins.When it comes to the pace of learning andupskilling, the key advantage of human-centeredtechnologies is that they are specifically designedfor “citizen access” rather than needing highlytrained specialists or depending on IT. Thisuniquely enables people to upskill themselves,but at a pace that is optimal for each individual.It makes each person’s upskilling journeypersonalized, creates an atomized learningexperience, and makes learning pervasive.6

E S S E N T I A L G U I D E T O A N A LY T I C P R O C E S S A U T O M AT I O N ( A PA )Digital Transformation Is No Longer An Elusive EndeavorThose organizations that have succeededin their digital transformation journeyhave taken a technology-first approachthat democratizes data, analytics, anddata science; enables optimizationand automation of business processes;and amplifies human output via ahumancentered experience. Now, allthree are achievable in one unifiedsoftware platform.In adopting platforms, organizations mustensure that the choice of platform deliversvisible business outcomes in the form of“quick wins.” These quick wins rationalizedeeper investments and confirm it’s asure path to transformation success. Withthe right technology platforms, over 80%of users see quick wins and measurablebusiness value in the first 14 days ofexperiencing the platform.Companies that invest in end-to-endautomation platforms will experience anacceleration of insight-driven decisions,extend the reach of their analytics andprocess automation programs, and builda sustainable competitive advantage."Research Director, AnalyticsEnterprise Management Associates7

E S S E N T I A L G U I D E T O A N A LY T I C P R O C E S SAUTOMATION (APA)The Catalyst forTransformationAnalytic Process AutomationThe need to accelerate the democratization of dataand analytics, optimize and automate businessprocesses, and enable fast upskilling of people inone unified approach has driven the emergence ofa new category of software called Analytic ProcessAutomation (APA).Analytic Process Automation platforms convergethree key pillars of digital transformation toenable the democratization of data andanalytics; the automation of business processes;and the upskilling of people to acceleratebusiness outcomes.Analytic Process Automation is distinct in thatit puts business outcomes first. Every businessobjective and outcome achieved with APAconverges all three critical organizational assets:data assets, critical business processes, andpeople’s domain knowledge.How Analytic Process Automation isAccelerating Digital TransformationTraditionally, a myriad of tools would be requiredto discover data, prepare data, analyze it, and applydata science algorithms and machine learning.Additionally, the business process for the analyticalworkflow would entail manual handoffs betweenteams, breaking the “flow” and slowing down theability to achieve meaningful outcomes.Analytic Process Automation is a comprehensivesolution that unites those disparate activities into asingle end-to-end automation platform.8

E S S E N T I A L G U I D E T O A N A LY T I C P R O C E S S A U T O M AT I O N ( A PA )Analytic Process Automation enablesthe transformation of entire businessinitiatives such as the following: Daily merchandising, sales, and supplychain optimizationAnalytic Process AutomationProven Organizational Impact#1 Faster analytic and data scienceoutcomes for actionable businessdecisions Continuous healthcare improvement,including monitoring, risk assessment,and intervention#2 Fully-optimized and automated Customer lifetime value (LTV) analysisand churn prediction#3 An engaged workforce that Tax and audit automation Predictive part failure and prescriptive(proactive) maintenance Automated liquidity and trading analysisfor agile financial portfolio optimizationintelligent business processesexperiences fast, self-serviceupskilling to drive greater outcomes#4 Capital-efficient digital transformation#5 Measurable ROI across four keyareas: top-line growth, bottomlinereturn, efficiency gains, and rapidworkforce upskillingAs a global bank, our clients count on usfor solutions and advice. To meet thesedemands, data is critical to our digitaltransformation initiatives. Integratedautomation platforms enable us to notonly accelerate our analytics and datascience to provide the best qualityservice and automate many processes,they also upskill thousands of peopleacross the bank and allow them to addeven more value."Director Data ScienceUBS9

E S S E N T I A L G U I D E T O A N A LY T I C P R O C E S SAUTOMATION (APA)Analytic Process Automation (APA) is distinct fromRobotic Process Automation (RPA) and the twoshould not be confused, although they integrateand are complimentary. For instance, APAplatforms can receive inputs and data from botsand output analytics outcomes to bots that thencan take automated actions such as enteringdata outcomes directly into enterprise applications.APA platforms automate entire data- andanalytics-centric business processes, with a distinctvalue and purpose. Organizations using APAwould say it provides more than 80% of theautomation value when the two are used together,while bot-based automation might provide theremaining 20%. This, of course, is highly dependenton the use case.10