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THE INTERNATIONAL JOURNAL OF APPLIED FORECASTINGTHE INTERNATIONAL JOURNAL OF APPLIED FORECASTINGARTICLES by FORECASTERSfor FORECASTERS: issue 63Integrated Business Planning: A New Narrativefor an Old ProcessJoin the Foresight readership by becoming amember of the International Institute of available to you with permission from the publisher

Forecasting and Planning PerspectivesIntegrated Business Planning:A New Narrative for an Old ProcessNIELS VAN HOVE AND HEIN REGEERPREVIEW Integrated Business Planning (IBP) has been a valuable business process since itsincarnation as Sales & Operations Planning in the mid-1980s. The monthly cycle of S&OPmeetings has been the forum in which a firm’s forecasts have been presented and reconciledacross functional areas. Authors Niels van Hove and Hein Regeer explain that while planningand forecasting technologies have benefitted from significant innovations since then,today’s IBP seems unhinged from the day-to-day operations of the business. They call for areinvention of traditional IBP that more fully integrates its governing meetings and reportinginto operations, enabling faster decision making, better responsiveness to disruption, andliberation for planners to work on more strategic issues.TRADITIONAL IBPAND PLANNING TECHNOLOGYIf we look back over the history ofsupply-chain planning, we can properlysay we are in the third wave of integratedsupply-chain planning software (Van Hove,2019). Wave 1, Enterprise Resource Planning(ERP), started in the 1980s with a focuson automating transactional businessprocesses, but less so on planning. Wave 2, Advanced Planning Systems(APS), first adopted in the 1990s, facilitated a forward view of the business, integrated plans with other functions, andoptimized supply-chain metrics such asforecast accuracy, inventory holdings,and customer service. Wave 3 systems, now gaining momentum, will provide intelligent automation that replaces the human planningprocess as well as cognitive automationthat augments a planner’s decisionmaking with predictions, insights, andrecommendations.Wave 3 systems will enable fully automated planning, decision making, andexecution. By bringing together severaltechnologies that have matured separately over the last decade, it is becoming asystem of intelligence, seamlessly integrating the following capabilities:46 FORESIGHT 2021: Q4Integration and harmonization of data from internal and externalsources, with transactional data selfcleansed and planning parametersself-maintained. Automation of descriptive, diagnostic,predictive, and prescriptive analytics,including self-selecting machine-learning models for a library of predefinedproblems. Smart process flow through a digitaltwin that can be configured to mimicany business user during forecasting,planning, decision making, and execution processes. Prescriptive analysis and recommendations that provide business users withadvice on why, how, and when to act. Automatic decision making and writeback of actions to underlying systemsof record. Digitization of every decision made, using an automated loop that learns fromboth human and machine decisions.At about the same time that Wave 2 wasgaining momentum, we saw publicationof the book Enterprise Sales & OperationsPlanning: Synchronizing Demand, Supplyand Resources for Peak Performance(Palmatier and Crum, 2002). The authorsdetailed a sequential S&OP cycle around a

New Product Review, a Demand Review,a Supply Review, and a ManagementBusiness Review. Figure 1 is an imagefrom the cover of the book.A whitepaper by Coldrick, Ling, andTurner (2003) entitled “Evolution of Sales& Operations Planning – From ProductionPlanning to Integrated Decision Making”presented the five-step process – shownin Figure 2 – which is still the foundationof most planning processes today, eventhough the scope of S&OP has expandedinto IBP.In his 2009 Foresight article, Bob Stahl emphasizes the five-step sequential monthlyprocess. Similar to the other publications,he asserts that executive S&OP is firstand foremost a decision-making process.The planning processes and governingS&OP meetings described in these publications have been widely implementedacross the world, supported by Wave 1and Wave 2 planning technology. Thesetechnologies focused on transactions,planning, and insights, but were neverbuilt for automated planning, decisionmaking, and execution. Many of today’sIBP processes are still rooted in thisprior generation of planning concepts,reflecting a notable absence of progress,especially considering that supply-chainexecutives expect to see autonomous supply chains by 2025 (Steinberg, 2019).Autonomous supply chains, where decisions and actions will largely be made bymachines rather than by humans, cannotbe realized by Wave 1 and Wave 2 systemsas these systems are aimed at automatingprocesses rather than decisions. To become autonomous, supply chains requirethe new technology of Wave 3 planningsystems, which we think of as systems ofintelligence.Key Points M any IBP cycles around the world are basedon a 20-year-old process definition supportedby 20-year-old planning concepts. Thistraditional IBP is not set up for a fast-changingworld, where speed of decision makingconfers a competitive advantage. New Wave 3Technology can empower a more efficient andresponsive planning process. W e propose that IBP be segmented by decisiontype into execution, operational, planning,and strategy/culture. For the execution andoperational decisions, modern planningtechnology can largely automate processesand decisions. For the longer-term decisionson planning and strategy, technology willaugment the quality of human-centricdecisions and nurture human-machinecollaboration. I BP should be converted from a separate,sequential, monthly planning cycle to anintegrated component of day-to-day business.This will be feasible as new technology enablesmore autonomous decision making, freeingthe planner to focus more fully on designingpolicies and targets.Hove, 2016). However, we’ve seen theshortcomings of these processes as well,including reliance on old technology.Figure 1. The IBP Cycle According to Palmatier and CrumLIMITATIONS OF TRADITIONAL IBPAs IBP managers, we have facilitatedwell over a hundred IBP meetings and,as consultants, we have implementedIBP processes across many countries andcompanies. We acknowledge the value ofIBP in support of an organization’s effortto deploy and execute its strategy (Van FORESIGHT47

Figure 2. The Five Key Steps of Integrated BusinessManagement / Integrated Decision MakingWhile IBP comes in many shapes andforms, it is based on a few foundationalconcepts. Cross-functional, human decisionmaking. IBP seeks to align key stakeholders from multiple functions on “asingle version of the truth”; that is, acommon understanding of mattersthat need to be addressed and the collaboration needed in decision making. Periodic planning cycles. Most common is the weekly Sales & OperationsExecution (S&OE) cycle to addressimmediate operational issues, and amonthly cycle for medium- to longterm issues. This dichotomy facilitatesresponsiveness in short-term planningwhile freeing senior management tofocus on high-impact decisions overthe longer-term horizon (and only byexception on operational issues). Sequential process steps. Both theweekly and monthly cycles follow astrict cadence of sequential meetingsand activities. The outcome of one step(for example, the Demand Review) isrequired input for the next step (SupplyReview). An IBP team typically drivesthe process and strives to maintain adherence to it within the organization.While these general concepts are straightforward, implementation can be challenging. Even after decades of experience, companies struggle with persistentshortcomings: Excessive focus on short-termissues. Despite weekly S&OE meetings for operational issues, IBP meetings still become distracted by acute48 FORESIGHT 2021: Q4short-term issues. And even thoughthe planning is designed to encompassa rolling 24-month horizon, IBP discussions are heavily skewed toward thefirst few months. Information and process focus,rather than decisions focus. ManyIBP meetings take on an “information sharing” character rather thana decision-making focus. The meetings should mark the moments in themonth where we “synchronize thewatches” in terms of demand and supply plans. Because IBP managers areincentivized to adhere to the process– follow the agenda, attendance, dataavailability and standardized templates– the time spent policing process compliance steals from the time devoted tohigh-value decision making. Limited attention to high-valuedecision making. In a traditional IBPcycle, there may not be adequate timeto prepare advanced simulations andbusiness continuity plans, or to seekcross-functional alignment in timefor executive-level decision making.One of the key reasons is the excessivenumber of meetings. Excessive meetings. Typical IBPcycles span a month’s time, but thiscan stretch to six weeks because of premeetings in which we prepare for meetings. Planners are now committed toprepare for the pre-meeting and thenreplan for the real meeting, all whiletrying to keep stakeholders aligned. Itis not uncommon for an IBP meeting totake four to eight hours. Inability to deal with disruptions.In IBP cycles that span many weeks,executives cannot respond quickly tomarket disruptions. COVID exposedthe inability of companies to makerapid strategic choices, such as in daysor weeks – impactful decisions suchas closing a factory, entering or exiting a product category, or reallocatinglimited resources in their supply chain.Some companies actively bypassed IBPby installing executive-led COVID warrooms to more rapidly implement strategic decisions.

Figure 3. IBP Segmentation by Planning Horizon, Automation, and Augmentation Lacking insights. Meeting notes andactions might be published after everyIBP meeting; however, actions and outcomes are often not properly recorded,not measurable, or not easily accessible.This omission limits continuous learning and restricts the creation of corporate insights around decisions. Was theplan the right plan and the decision theright decision under the circumstances? Was the right action taken by theproperly authorized person?The authors believe these shortcomings can largely be addressed by aligningthe IBP process with Wave 3 planningtechnology.MACHINE-CENTRIC VSHUMAN-CENTRIC DECISION MAKINGWhile IBP has become nearly synonymouswith “the S&OP monthly cycle,” therereally is no compelling justification forthis monthly frequency. By automatingaspects of the process, Wave 3 technology can decouple decision making fromthis arbitrary cadence, allowing plannersto concentrate more fully on goal settingand oversight of policies and systems,while providing the knowledge augmentation for these human-centric decisions.Planning HorizonsThis new technology will support decisionmaking in different planning horizons.In earlier Foresight articles (Van Hove,2020, 2021), Niels distinguishes decisionautomation from knowledge augmentationand examines the relative desirability ofthese features across different planninghorizons. Longer planning horizons, forexample, require human-centric decisions, while shorter-term operational decisions are more amenable to automation.Figure 3 summarizes the possible enhancements to IBP from Wave 3 technology. The key is to segment IBP along decision type and then differentiate betweenmachine-based IBP, which runs underhighly automated planning and decisionmaking with human involvement only byexception, and human-centric IBP, whichwill benefit from decision augmentationand human-machine collaboration.Machine-Centric IBP DecisionsAs shown in Figure 3, machine-centric decisions will be well suited for automationof both Sales & Operations Execution(S&OE) and Operational IBP.In the short-term horizon (0-3 months),operational decisions are frequent, repetitive, low value, and granular (e.g. atthe SKU/location level). These includedemand and supply balancing, inventorychange, order purchase and allocation,stock transfer, and product pricing. Suchdecisions require limited human alignment and sign-off. Hence, they can beautomated to sense change or disruptionin the supply chain and respond to it.Humans will still set policies and rules tostructure the automated process.Operational IBP decisions (4-12 monthsahead) are less frequent and time urgent than in the S&OE horizon, but stillhave low impact/value and apply at adetailed level so that planning and decision making can be automated as well. FORESIGHT49

Demand-planning tasks, including datagathering and cleansing, statistical/MLforecasting, and detection of variancesto targets and budgets, can be actionedautomatically with only limited humanmachine collaboration required. Humaninput will be required to set goals andpolicies to help the machine optimizepromotions, price settings, and phasingof new-product introduction to reach certain targets.Supply-planning processes in this horizon can be partly automated. Due to thelonger decision horizon and higher uncertainty, supply-planning decisions becomemore probabilistic in nature, and so willbe amenable to medium levels of automation and augmentation.Based on demand input, optimized supply plans can be automated to run concurrently across an entire network and provide planning outputs for distribution,replenishment, and production. Evenchanges to planning parameters such aslead times, safety stocks, capacities, andbatch quantities can be automaticallyupdated, and gaps to service levels or coststructures in the supply chain will be detected and actioned automatically.Many operational decisions that mightlook complex can be solved through business rules, machine learning, and probabilities. For example, when planning tointroduce a new product to the market,the system can calculate a probability ofhitting the introduction date and so automatically update the phase-out planningof the predecessor product.For both machine-centric IBP segments,while many decisions can be automated,decisions above a certain value or probabilistic threshold will require crossfunctional collaboration and sign-off. Yetcross-functional meetings can becomemore agile by acting upon exceptions suggested by the machine.Human-Centric IBP DecisionsPlanning decisions in this category address higher levels of aggregation (e.g.product families) and normally havehigh impact/value. Since these decisionsare more complex, they require human50 FORESIGHT 2021: Q4alignment and sign-off and so are lessamenable to automation. The role of themachine is to support the planner in decision making, resulting in human-machinecollaboration.The machine can support the plannerwith probabilistic simulations and what-ifscenarios, network or price optimization,multisourcing, new-product development, and innovation updates. It willdetect gaps in revenue, margin, or costversus targets and budgets automaticallyand provide recommendations for gapsclosure. These recommendations will beactioned functionally for the most part, aspre-agreed policies and functional tradeoffs have been incorporated in the recommendation. In this way, IBP will morphinto an aspect of business as usual ratherthan a distinct and dogmatic process.At the strategic level, decisions are complex, infrequent, and high in granularity, as well as in value/impact on thebusiness. They can also be cultural andvalue-based, requiring human alignmentand sign-off at the executive level. Thesedecisions are too complex and importantto be automated, and they likely requirehuman capabilities that the machinedoesn’t possess. The human-centric nature of strategic IBP decisions means thata greater emphasis should be placed ongovernance – that is alignment, decisionrights, rewards, and culture (Sorenson,2020) – instead of automation.Machines, however, can develop recommendations for executives around strategic scenarios, mergers and acquisitions,network risks assessments, geopoliticalwar games, category changes, onshoringversus offshoring, and large CAPEX investments, thus providing probabilitiesand financial impacts.A NEW SET OF IBPCONCEPTS AND ASSUMPTIONSSegmented by decision type as is Figure 3and supported by new Wave 3 technology,the new IBP will improve a firm’s ability to address many traditional IBP challenges and create structures that are farmore aligned with current times. Theseare summarized in Figure 4.

Figure 4. Impact of Wave 3 Technology on IBPTraditional IBP ChallengeMachine-Centric and Human-Augmented IBPExcessive focus on short- term issuesWave 3 will enable a highly automated S&OE horizonimplemented by rule-based machine learning.Overly long planning process &decision cycleIBP will be more integrated in day-to-day business meetings, with the option to call special meetings to deal withfast-breaking crises.Information rather than decisionsfocusDescriptive and diagnostic IBP analytics will be providedautomatically and made available at all times throughoutthe business.Process compliance rather thandecision focusIBP teams will be incentivized to provide strategic businessscenarios and improve automated decision making ratherthan to police process compliance.Significant resource requirementsMost analytics and planning will be automated, reducingtime spent in meetings, freeing up planning resources.Lack of attention to high value andstrategic decisionsTime freed up through automation can be spent on big-ticketitems such as business contingency planning and supply-network resilience planning.Inability to deal with disruptionProbabilistic simulations will predict disruptions with opportunity to prevent or prepare for them. Special IBP meetings canbe held to deal with urgent matters, and decision automationcan be dialed down when there is significant disruption predicted. Decision augmentation can be dialed up to simulateimpact of disruption.Lack of insightsWave 3 technology will capture and digitize every corporatedecision. The history of IBP decisions/impacts will be availabledigitally to learn from and guide future decision making. Thiswill enable putting metrics and rewards in place to drive cultural change around decision authority and accountability.To start the transition to this new typeof IBP, we need to establish a fresh IBPmindset, supported by new aspirationsand assumptions. We suggest replacingthe foundational concepts discussed earlier by the following:Data and Analytics IBP will automatically gather andcleanse relevant internal and externaldata and distribute these across thebusiness in one common data layer,near real time. This will permit sales tochange prices and demand forecasts upto a certain threshold (say 25%) w/oconsulting finance or operations. It will automatically provide descriptive and diagnostic analytics and makethese available at any time throughoutthe business.Planning Planners will guide the machine withpolicies, goals, and targets. Planning will take place continuouslyand require human input only uponmatters that exceed certain impact orcomplexity thresholds. The machine will identify variationsand gaps to plan and automatically action these up to a defined threshold.Above that threshold it provides recommendations to be decided upon byhumans.Process & Meetings The frequency and duration of IBPmeetings will be driven by decision requirements, not process requirements. IBP teams will be incentivized to provide strategic business scenarios andimprove decision making, not to policeprocess compliance.Decisions & Execution IBP decisions and impacts will be recorded digitally, applied to self-learning,and accessible to all IBP stakeholders. FORESIGHT51

Such decisions will be executed automatically where possible, as all contextual information available will bestored. Human adjustments made to the system-generated recommendations willbenefit from feedback, reducing theimpact of human biases.For a company to transform from a traditional planning process to one segmentedby human and machine decision makingcan be quite a journey. Changes will berequired to operating models and systems, roles and organizational structure,rewards, and incentives. Additionally,planner capabilities will need to adjust tocollaboration with the machine. Still, itcan be done.During COVID, the global CPG giantUnilever compressed its planning cyclesfrom four weeks to one week, then tothree days. It now combines human andmachine aspects in its organizationalstructure with machine reporting to ahuman. It has clearly defined when thehuman is in the loop, on the loop, or outof the loop in decision making. Unilever’sapproach may pave the path to the newnorm for IBP.CONCLUSIONThe traditional IBP process and supporting Waves 1 and 2 planning technologiesare a generation old and incapable of effectively adapting to today’s challengesor taking advantage of innovations intechnology.Long overdue is a reset of traditional processes to approach IBP from a decisionperspective. Supported with today’s systems of intelligence, we can assess wherethe machine should automate decisionsand where the human will guide the machine and lead in decision making. We canthen integrate IBP into day-to-day business meetings, rather than maintain it asa separate planning process.REFERENCESLing, D., Coldrick, A. & Turner, C. (2003). Evolutionof Sales & Operations Planning – from ProductionPlanning to Integrated Decision Making, s opevolution.pdfPalmatier, G. & Crum, C. (2002). Enterprise Sales &Operations Planning: Synchronising Demand, Supply andResources for Peak Performance.Sorensen, D. (2020). Strategic IBP: Driving ProfitableGrowth in Complex Global Organizations, Foresight,Issue 56, BP-Sorensen-Winter-2020.pdfSteinberg, G. (2019). How Reinventing the SupplyChain Can Lead to an Autonomous Future, https://Niels van Hove is a Client Engagement Principal at Aera Technology. He uses his more than20 years of supply-chain experience to guide clients toward a more autonomous process. See our“Forecaster in the Field” interview with Niels in theSummer 2016 issue.niels.vanhove@aeratechnology.comHein RegeerHein is a Client Partner withAera Technology, and works with large companies to digitize, automate and augment SupplyChain decision making. He has over 25 years ofexperience in driving improvements in complex, international supply chain environments.Hein worked as global manager IBP & Demand Planning atJDE Peets, the world’s largest coffee & tea group . As a consultant Hein delivered technology-enabled programs inS&OP, Planning, Logistics and Strategic Network Design.hein.regeer@aeratechnology.com52 FORESIGHT 2021: -lead-to-an-autonomous-futureVan Hove, N. (2021). Commentary: AI Is Here toAutomate the Knowledge Worker, Foresight, mment.pdfVan Hove, N. (2020). Technology Support in BusinessPlanning: Automation, Augmentation, and HumanCentricity, Foresight, Issue 58, usiness-planning-article.pdfVan Hove, N. (2019). Autonomous or “Lights Out”Supply Chain Planning: What New Technology IsRequired, Foresight, Issue 33, dfVan Hove, N. (2016). An S&OP CommunicationPlan: The Final Step in Support of Company Strategy,Foresight, Issue 42, /07/issue42vanhove.pdf

monthly cycle for medium- to long-term issues. This dichotomy facilitates responsiveness in short-term planning while freeing senior management to focus on high-impact decisions over the longer-term horizon (and only by exception on operational issues). Sequential process steps. Both the weekly and monthly cycles follow a

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