If you work for a large organisation, chances are you're no stranger to enterprise resource planning (ERP). Many large companies have spent 30 years automating their operations and the past five years replacing these investments with ERP systems. While these systems have produced cost savings in terms of reduced head count, shorter payment cycles and faster inventory turns, they are reaching their limits of competitive value. Not only because every business uses them but also because they fail to continuously increase revenue or affect strategic advantage. Why? Because ERP automates business processes but doesn't enable organisations to improve them once the software is up and running. In addition, ERP systems typically don't affect the processes that directly contribute to revenue like marketing, sales and customer service. So you can automate the business with ERP, but you can't optimise it.
Despite its other strengths, ERP can't prepare businesses for the wrenching changes that the Internet brings. Only relentless self-improvement will enable them to adapt and thrive in the Internet economy. Therefore, companies need to rethink their businesses to proactively seize market opportunities by targeting the right customer, pricing for customer profitability and delivering one-to-one customer service. Frontline decision making can help achieve that end.
Frontline decision making is the process by which companies automate decision processes and push them down into the organisation and out to partners. It includes devising strategies, evaluating metrics, analysing impacts and making operational changes. Analytic application products are now emerging to support these actions.
Frontline decision making serves business users such as line managers, sales executives and call centre reps by incorporating decision making into their daily work. These workers need applications to help them make good operational decisions that meet overall corporate objectives. Today's decision-support tools alone can't fill this need because they fail to give users enough context to make better decisions. Frontline decision making provides users with the right questions to ask, the location of needed data and metrics that translate data into corporate objectives, and suggests actions that can improve performance.
Forrester believes adopting frontline decision-making practices is essential for organisations to continue ratcheting up employee productivity, customer profitability and business success.
Empower Decision Makers
Decisions at all levels in the organisation contribute to the success of the business. But decisions that maximise a sales opportunity or minimise the cost of a customer service request happen on the front lines. Those closest to situations that arise during the course of daily business, whether it be an order exception, an upselling opportunity or a contract that hangs upon a decision, must be able to make effective decisions rapidly, based on context and according to strategies set forth by senior management.
Today's transactional applications and decision-support tools don't readily enable frontline users to make better decisions. Systems like those from SAP AG and Siebel Systems don't implement simple decision processes or present data in a way that can be analysed for complex decisions. Executives may get context from reports and systems created for them (like financial or executive information systems), but these don't provide frontline workers any guidance on daily problems. Meanwhile, traditional decision-support tools and servers from vendors like Cognos, Oracle and Business Objects SA are intended for experts -- those who can access data, slice and dice it, and give it business meaning -- unlikely to be at the front lines. So organisations need a new generation of enterprise analytic applications to implement frontline decision making by posing intelligent questions, building business context and determining optimal outcomes.
In frontline decision making, every operational process has a corresponding decision process for evaluating choices and improving execution. For example, order management has cross-selling suggestions and a customer service representative could offer additional items to customers based on their specific needs. If my telephone company has frontline decision making, when I call about a service issue, the person I speak to knows I have call waiting. From that and my profile characteristics, the rep is likely to offer me caller ID, explaining that I'd be able to see who a second caller is when I'm still on the line. Having frontline decision making enables the company to make better cross-selling suggestions by tailoring a response to me. A customer service rep without this capability would make cross-selling suggestions based on this week's special, regardless of my individual needs.
Frontline decision making automates simple decisions -- like freezing the account of a customer who has failed to make payments -- by predefining business rules and events that trigger them. At more complex decision points, such as inventory allocation, frontline decision making gives managers the necessary context -- available alternatives, business impacts and success measurements -- to make the right decision. In order for business users to take advantage of ordinary decision support, they have to know the questions to ask, where the information resides and the components of any metric. In frontline decision making, users are given context set up by senior managers (for example, allocate inventory to premier customers first, then next level and so on) and can be alerted when exceptions arise (for example, orders and demand forecasts show inventory levels will fall short of serving premier customers this month).
Good decision processes enable a company to constantly evaluate its strategies and fine-tune operations based on recent events and future expectations. Organisations should enable call centre reps to cross-sell to customers based on a customer's history as in the example above. Or, as in the case of Australia Bank, when certain events occur -- such as a customer making a withdrawal 100 per cent larger than her average withdrawal -- a telemarketer is alerted and informed about how the customer prefers to be contacted. The telemarketer can then reach out to the customer to understand the situation and attempt a cross-sell if appropriate.
Frontline decision making enables organisations to apply metrics, like customer profitability, across the enterprise, thus uniting various functional departments around a common goal. For example, frontline decision making will analyse an existing customer's profitability, and by analysing recent trends like fluctuations in purchasing or service failures, will suggest ways for sales managers to improve service and retention probability. It may prompt sales managers to offer special rebates or premium levels of service -- offers they would not make to unprofitable customers.
Companies must not only help line managers and knowledge workers make good decisions but also help them understand the impact their decisions have on overall company success. Measuring results of decisions in light of larger goals, and reporting results to the decision makers, is therefore extremely important.
These applications will solve specific problems by packaging into a single browser-based self-service framework the required business logic (including business rules that map to objectives, algorithms that capture optimisation opportunities and sequencing scenarios), metrics (such as return on assets, customer retention rates or product life cycle expectancy) and decision workflow (which analyses and ranks alternatives, and ties together logical steps in the decision process so that users can initiate action).
These applications need to be browser-based because the audience using them often includes remote users who need to access the most up-to-date information. To be successful, frontline decision making applications must work hand in glove with transactional systems, accessing records of events or pulling business context from sources such as best practices repositories and content databases.
Many vendors are popping up, the best known being Hyperion Solutions, SAS Institute, Epiphany, NCR and i2 Technologies. Aside from a few old-line financial application suppliers, there is an open opportunity for vendors with domain expertise and technology excellence. Forrester believes the technology will evolve over the next five years in direct proportion to the transaction systems market.
Phase 1: Collision (1998-2001). In the next 18 months, three types of vendors will fight for a place in the analytic apps market. Tools vendors like Brio Technology and MicroStrategy, enterprise players like J D Edwards and Siebel, and niche vendors like Deploy Solutions and AlphaBlox will collide as they compete for attention. Front runners will provide an integrated solution including extraction, analysis, decision workflow and personalised presentation.
Phase 2: Consolidation (2001-2003) This phase will consolidate both technology and functional areas, and niche players like BroadQuest and Icarian will become acquisition targets. Technology will converge on standard platforms like Microsoft and Oracle, and market momentum will drive vendors like Hyperion and Parametric Technology toward complete functional coverage. Vendors must establish analytic platforms and branch out from one functional area to cover all of the front office.
During this phase, vendors will support complex, cross-departmental decision processes. That will force them to incorporate best practices like Norton and Kaplan's Balanced Scorecard and external content like Axciom's marketing database. Closing the loop between operational decision making and execution will be critical in this phase, giving a leg up to vendors with integration expertise in key transactional apps like those from PeopleSoft and Lawson Software.
Phase 3: Cohesion (2003+). By 2003 leading vendors will emerge in four functional segments: strategic planning, customer analysis, asset management and product analysis. Companies will be able to buy enterprise analytic apps that optimise strategic planning for executives and translate those strategic plans into organisational metrics and processes that business users can enforce and execute. Finally niche vendors will become industry focused, analytic app leaders emerge and decision-support tools get driven out. Enterprise analytic app vendors like i2 and SAS will achieve dominance by their support of strong systems integrator partners like Ernst & Young LLP and KPMG LLP.
Next Steps for Users
To gain the greatest competitive advantage, companies should immediately begin implementing analytic applications for front-line decision making. The benefits of increased customer loyalty, decreased operational losses and more effective management will outweigh the cost of implementation in the turbulent early going. When Australia Bank installed NCR's relationship optimiser to make its telemarketing more effective, for example, it resulted in increased sales opportunities. To buffer the risk of vendor failure and technology shifts, companies should choose applications that solve immediate business needs like online selling or sales territory management. As business needs increase, they can add modules or create custom modules on the vendor's technology platform. Companies should choose vendors that can provide value out of the box -- browser-based solutions with pre-packaged reports, analytic capability and workflow options.
These integrated products will take most of the implementation burden off users. Most modules come pre-packaged with about 35 reports and decision processes that would be applicable in a given industry, and companies usually add about 10 or 15 that are specific to their needs. Many of these have a "create reports" option that lists all the criteria so that business users could easily create their own.
With an increased focus on analytic applications, companies should reconsider future ERP investments. Analytic applications will force organisations to bring together operational data from many applications into a consistent view. As a result, managers can accurately analyse the business without an all-encompassing ERP platform. Therefore they should re-evaluate their need for an ERP system and implement modules only when the added capability creates competitive advantage.
One last thing can't be neglected: To implement decision making effectively, companies must hire middle managers with strong analytic capabilities who can translate strategic plans into operations for the front line. These managers should be able to identify and synthesise metrics to fine-tune frontline operations. And with greater efficiency and coordination with corporate strategy, the front line will help the bottom line. vStacie McCullough, a business applications analyst with Forrester Research in the US can be reached at firstname.lastname@example.org
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