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An extended Value Chain model for performance Prediction and Optimisation of product and process Lifecycles for SMEs

Final ReportSummary - VALUEPOLE (An extended Value Chain Model for Performance Prediction and Optimisation of Product and Process Lifecycles for SMEs)

In order to thrive in the 'new real economy' small and medium sized enterprises (SMEs) face two performance objectives; they need to be efficient and innovative to participate in the new knowledge based economy. Decision makers within SMEs face many competitive threats but also have a range of development opportunities available to them to advance the competitive position of their firm. These opportunities typically include development of new products and/or the improvement of their process performance. However, it is very difficult to decide, ex-ante i.e. before-the-event, to which combination of new product development and/or improvement opportunities the SME should devote resources for the firm to maximise its economic performance. This is of strategic importance, given the limited resources available to SMEs. The VALUEPOLE project addresses this challenge.

The primary objective of VALUEPOLE was to develop and implement an ICT tool with a supporting model and methodology. VALUEPOLE supports decision making at operational, tactical and strategic levels within the SME. The VALUEPOLE tool prioritises the best value improvement opportunities for the SME practitioner from a portfolio of potential new products or process improvements. This enables the decision maker to rapidly identify the risk / reward position of any project or combination of projects vis-à-vis a suite of pre-defined key performance indicators.

In order to deliver the overall objective, the science and technology had to developed, particularly in the areas of enterprise modelling, predictive performance management, simulation and optimisation. The VALUEPOLE project has delivered 4 main project results for the benefit of the SMEs, including the following:

- A market demand response model which provides the SME decision maker with a coherent understanding of the market needs in the short term for current products as well as in the long term for new products. This allows the end-user quantify the potential consequences on the enterprise KPI's portfolio for a diverse range of market demand scenarios so they can be considered at the appropriate decision points throughout the new product development life cycle.
- An ex-ante predictive performance modeller for SMEs which enables the practitioner (a non-ICT expert) to succinctly describe the capabilities of the enterprise for its key performance indicator (KPI) portfolio. This enables the VALUEPOLE tool to be used to model the consequences of the most critical product and/or process improvement lifecycle decisions.
- A performance improvement project (PIP) model and optimisation tool which enables the practitioner to create and manage a portfolio of process performance improvement projects in VALUEPOLE with the goal of maximising the enterprise operational performance against a suite of KPIs.
- A new product development project (NPDP) portfolio model and optimiser which will enable the user to monitor via a rich user interface in VALUEPOLE the performance indicators for the portfolio of NPDPs within the enterprise.

The VALUEPOLE project has delivered an ICT Tool and a methodology for SME decision makers to maximise their competitive position with the minimum investment of resources. The results will be commercialised by the SME partner ManOPT Systems Ltd., in their new-to-market flagship product: MAKE. (see http://www.manopt.com for details).

The SME manufacturing demonstrators in the consortium have continued to thrive throughout the project, despite the tough economic climate currently for SME manufacturers. Specifically, with the assistance of the VALUEPOLE project, one SME has doubled its employed and tripled sales (+200 % sales) in export markets. A second SME has doubled sales and won back business for the EU that had been previously subcontracted to China. The SME end-users report that they have exceeded benefits of greater than 5 % of revenue.

Project context and objectives:

In order to thrive in the 'new real economy' SMEs face two performance objectives; they need to be efficient and innovative to participate in the new knowledge based economy. Decision makers within SMEs face many competitive threats but also have a range of development opportunities available to them to advance the competitive position of their firm. These opportunities typically include development of new products and/or the improvement of their process performance. However, it is very difficult to decide, ex-ante i.e. before-the-event, to which combination of new product development and/or improvement opportunities the SME should devote resources for the firm to maximise its economic performance. This is of strategic importance, given the limited resources available to SMEs. The VALUEPOLE project addresses this challenge.

Competitive advantage and sustainability for European manufacturers require that they are competitive in many domains (Manufuture, 2006). Traditionally a manufacturer would be competitive if they produced a product that met the quality, cost and delivery requirements of the market. Today and in the next decades, European industry in general, and SME firms in particular, are presented with many seemingly conflicting performance objectives:

1. improve efficiency in the entire value chain in order to meet 'better, cheaper, faster' competitive objectives;
2. meet 'greener, safer, securer' EU socio-technical policy objectives;
3. while simultaneously juggling strategies for incremental and breakthrough innovation in product and process development.

When an SME decision maker currently reviews his operational, tactical and strategic options, in light of the above, he currently relies on his own empirical knowledge and judgement. Prior to this project, there existed a theory practice gap in the provision of decision support tools for SME practitioners in this domain.

The primary objective of this consortium was to develop and implement an ICT tool with a supporting model and methodology. The tool has to support decision making at operational, tactical and strategic levels within the SME. The VALUEPOLE tool prioritises the best value improvement opportunities for the SME practitioner from a portfolio of potential new products or process improvements. This enables the decision maker to rapidly identify the risk / reward position of any project or combination of projects vis-à-vis a suite of pre-defined key performance indicators. VALUEPOLE, has delivered:

- a new predictive performance tool for SMEs, to maximise value creation in the entire product, process life cycles. (VALUEPOLE maximises value creation by providing an infrastructure for the ex-ante, i.e. before the event, prediction of performance outcomes in planned innovations).
- a model for performance prediction and optimisation of the product and process lifecycles in SME value chains.
- A methodology that goes 'beyond lean' in that it enables organisations to better deploy its resources to be both operationally effective through the selective application of improvement methodologies to current organisational configurations for today's customers as well as strategically flexible in the adaptation of new configurations of products, processes, technologies, competencies, and systems that enable the satisfaction of tomorrow's customers.

Project results:

In order to deliver the overall objective, the science and technology had to developed, particularly in the areas of enterprise modelling, predictive performance management, simulation and optimisation. The VALUEPOLE project has delivered 4 main project results for the benefit of the SMEs, including:

1) A market demand response model which provides the SME decision maker with a coherent understanding of the market needs in the short term for current products as well as in the long term for new products. This allows the end-user quantify the potential consequences on the Enterprise KPI's portfolio for a diverse range of market demand scenarios so they can be considered at the appropriate decision points throughout the new product development life cycle.
2) An ex-ante predictive performance modeller for SMEs which enables the practitioner (a non-ICT expert) to succinctly describe the capabilities of the enterprise for its KPI portfolio. This enables the VALUEPOLE tool to be used to model the consequences of the most critical product and/or process improvement lifecycle decisions.
3) A PIP model and optimisation tool which enables the practitioner to create and manage a portfolio of process performance improvement projects in VALUEPOLE with the goal of maximising the enterprise operational performance against a suite of KPIs.
4) A NPDP portfolio model and optimiser which will enable the user to monitor via a rich user interface in VALUEPOLE the performance indicators for the portfolio of NPDPs within the enterprise.

The following is a discussion of each of the four main results:

1. Market demand response model

In both the scientific literature and current state ERP systems, the demand planning focus is not on the individual customer order, but on the total volume achieved for a given planning period. This paradigm neglects the fact that demand is comprised of individual customer orders that may behave very differently than expected. The work conducted in VALUEPOLE takes two main directions; an explorative research oriented approach and a prototype tool oriented direction. The research direction has focused on data gathered from all the manufacturing partners of the VALUEPOLE project. Here, a broad approach has been used to evaluate all dimensions of demand as presented in a number of scientific contributions. The tool oriented direction has, in close cooperation with the end-users in the partner SMEs, focused on implementing the more robust analyses derived, validated and verified through the research work. This dual approach has given a robust set of analyses that have been tested and implemented in several of the participating companies. Furthermore, extensive field tests on data from companies outside the partner group, has validated the methods' efficacy and impact on business performance.

The research work has focused on identifying demand parameters critical to planning, their expected and actual behaviour and connecting this to delivery performance along the three dimensions revenue, volume and order lines on-time-in-full (OTIF). Parts of this work have been documented among other in the references included at the end of this section.

Through work with both the participating SMEs and other field experience, these analyses were condensed into four distinct dimensions of analyses for implementation: order size statistics, demand statistics, delivery performance and order book status. The analyses can for each dimension be narrowed to a given customer and/or product group or market.

Order sizes are a critical parameter when designing manufacturing environments. The number of orders and the distribution of the order sizes are used to facilitate the aggregation and disaggregation of plans and to achieve a proper line balancing. The consensus in literature is either to assume a constant number of orders and order size within a planning period or to assume that the order sizes are i.i.d. and stem from a symmetrical distribution. However, tests by the researchers in the VALUEPOLE project on data from several companies have shown the assumptions found in literature to be wrong. Through end user participation it was found that the SMEs need further insight into the order size behaviour. Especially to establish how much orders of given size contribute to the overall volume for a product family and if there has been a change in this in the short term versus the long term. This led to a number of analyses that can be used for:

- determining if the order sizes are distributed like assumed in e.g. the ERP-system (for capacity planning purposes) or for line balancing purposes;
- determining the service cost implicit in choosing to service big orders over small (V-OTIF versus OL-OTIF).

The order sizes are in the software tool displayed using the 'banana-graph', indicating how large a ratio of total demand is covered by a given order size and user defined tables with order sizes in the short and long term for specific products on given markets.

Demand statistics:

To give insight into specific markets a number of dimensions demand have been found to be very effective to present to the end user. Displaying demand in volume per week and per four weeks for the last 52 weeks in the form of confirmed sales orders for specific markets and product groups as graphs. The time periods of one and four weeks have been found to be relevant across several of the participating SMEs. Likewise it was found relevant to display a histogram of weekly demand for the last 52 weeks. This can be used to evaluate the distribution of demand and the volatility of demand per week, i.e. it can be used directly by e.g. the production manager to estimate buffering needs (on capacities, materials or delivery times). The 'broader' the histogram the larger the buffering needs. These visual displays were particularly effective when combined with descriptive statistics regarding the variation in demand for one and four week periods respectively.

Delivery performance statistics:

Through end user input it was found that the SMEs would like to have a graph of their 3D delivery performance with each of the OTIF measures displayed separately for a given area (product group and customer group / market). This information can be used internally in the SME to control the delivery performance for a given area (product group etc.) and instigate measures to improve delivery performance. The aggregate nature of the information makes it suitable for use in connection with overall evaluation and re-design of the manufacturing and delivery system. Depending on the filter used, the information will be more or less suitable for various functions within the company. The information is relevant when comparing the interaction and tradeoffs between the three dimensions of delivery performance. The use of three complementary OTIF measures enables the end-user to evaluate the tradeoffs involved in chasing one measure. Companies usually chose one measure over others. However, this tool is able to document the impact on other OTIF measures.

Order book status:

From end-user interviews it has been established that it is often critical to track the total content of the order book for given segment (market, product group, customer group etc.). To accommodate this requirement two graphs have been developed using the historical orders (order lines filtered according to one or more discriminators). One contains a day by day overview of the volume of the order book currently and the order book at the same time the previous year. The other graph contains the accumulated volume of the current order book content and the order book content for the same time the previous year. This report can be generated for any number of markets, customer groups, product groups and time horizons according to the user defined needs. Together these graphs enable the user to evaluate the current demand status, take appropriate measures (add / remove capacity, start / end promotions etc.). These graphs are typically suitable for distribution across and use in the whole organisation of the SME.

A main strength of the analyses developed and implemented is that while the structure of the data-sources will vary depending on the SMEs' systems, the data used in the analyses is generic. This means that the data is available in all major ERP-systems in a form suitable for use in the current analysis and reporting mode. This makes the methods highly useful for implementation in SMEs outside the VALUEPOLE project.

The developed software tool for market demand analysis has a number of features not seen in any other systems available today. These are:

- a novel 3D view on delivery performance;
- new ways to determine the stability of order sizes and help in determining changes to these;
- order book monitoring;
- full flexibility in the dimensions of data examined.

These features have enabled the participating SMEs to:

- focus on markets / products with poor delivery performance and the underlying behaviour of planning parameters;
- achieve valuable insight into the actual demand behaviour - in dimensions directly suitable for implementation in PIPs;
- attain the ability to view information by customer or product (groups) depending on the situation - and visually compare areas;
- and open their eyes to the fact that delivery performance is not just a one dimensional affair.

The multidimensional views enable new forms of interpretation of system behaviour and performance, enabling the practitioners in the SMEs to focus their energy where it matters.

Morsoe directly uses the 3D delivery performance measures to support their different market strategies. For the local Scandinavian markets, Morsoe aims at a high order line OTIF performance, while for other markets revenue and volume are more interesting dimensions. This tool has enabled Morsoe:

1) to actually see their delivery performance; and
2) to follow up where the performance is unsatisfactory.

Since delivery performance is a critical for Morsoe's market they use this information to improve their market position. Likewise Morsoe uses the order book feature to evaluate whether or not to intervene in their market at a given time with e.g. campaigns.

Due to the new methods and tools Morsoe has been able to:

- better understand their business performance;
- understand how their order sizes change over time and use this in their planning;
- focus on the products and markets that were causing problems and thereby improve their overall performance.

The data from Burnside has been run through all the analyses used to describe demand characteristics. In general, the demand analyses have shown to have a great impact on the understanding of the market and the demand conditions faced by the SMEs. The benefits for Burnside have been an increased insight into their demand characteristics, enabling them to:

- fine tune manufacturing lines;
- understand the dynamics of their various products;
- realise that their 60 % least sold products have a highly unstable behaviour, while the 1 % most sold are very stable; and
- understand that the accumulation of demand in a planning period is in fact seasonal (and that their planning should be adjusted accordingly).

All of this has enable Burnside to reduce the resources used in manufacturing by better matching their planning to their demand, thereby increasing the competitiveness.

2. An ex-ante predictive performance modeller

The second VALUEPOLE result is the ex-ante predictive performance modeller for SMEs which enables the practitioner (a non-ICT expert) to succinctly describe the capabilities of the enterprise for its KPI portfolio. This enables the VALUEPOLE tool to be used to model the consequences of the most critical product and/or process improvement lifecycle decisions.

Current management practice is that decision makers within enterprises review past (ex post) performance of existing processes and products and then select an improvement option based upon a limited, if any, quantifiable understanding of the probable outcome. This approach relies on data which at best is time-lagged and at worst irrelevant in a fast changing very competitive environment. Success in the future depends upon effective and timely decisions being made today; management need a futuristic view of what are the potential outcomes of their decisions are likely to be across a range of performance objectives as well as support in proposing strategies to meet those objectives.

The VALUEPOLE project enables practitioners to target decisions, new products and improvement efforts at quantifiable outcomes by utilising ex-ante performance predictions of a portfolio of KPIs from a range of alternate scenarios where the highest yielding new product or improvement techniques are clearly visualised. Ex-ante prediction models quantify what the performance outcome is likely to be before the event rather than relying solely upon empirical judgement of the decision maker.

A critical issue for the SME practitioners within the consortium was the need for a method to define the economic benefit for completing either a NPD project or a PIP as an alternative to not completing the proposed project. The solution proposed was that the SMEs needed a method of predicting the additional revenue contribution of the proposed new product or process improvement project. A key concern of the SMEs was that they would make the investment in a particular new product or process improvement project but not see the benefit show in the revenue performance outcome for the firm. This work represents a considerable advance on the state of the literature.

In VALUEPOLE, we first represent (model) the status quo position of the enterprise. This requires the prediction of the revenue position of the firm for the current enterprise state from:

- current sales order book
- current purchase order book
- current suite of open and planned work orders
- current suite of resources.

The current enterprise state performance is then optimised and the resultant sales order shipment schedule is used to predict the revenue performance of the firm. We then evaluate within actual firms the revenue predictions to verify that they conformed to the actual revenue performance. Next, we build a decision infrastructure where the differing scenarios can be generated. Once a proposed management intervention is proposed in the enterprise the associated changes are defined within the enterprise model. The new enterprise model version is run and the new optimised revenue is compared and presented to the decision maker. The visualisation of the potential revenue improvement is a critical theoretical and practical contribution to the SMEs and is in production within the normal operation of one of the SME partners.


3) A PIP model and optimisation tool

The third VALUEPOLE result is the PIP model and optimisation ttool which enables the practitioner to create and manage a portfolio of process performance improvement projects in VALUEPOLE with the goal of maximising the enterprise operational performance against a suite of KPIs.

The PIP-tool is based on are two different approaches. The first one is a reactive approach, ex-post, which is capable to calculate the consequence of parameter settings in an online transaction processing (OLTP) e.g. an ERP-system as well as the consequence of business priorities and behaviour in daily operations. The second is a proactive approach, ex-ante, which is capable to calculate consequences, evaluate and diagnose the business process and priorities of orders (customer, production and purchase).

We have developed a framework for diagnosing the problems related to a company's KPI and be able to develop the PIP-tool's usefulness. The KPI framework supports both an ex-ante and an ex-post approach. The two KPI approaches are based on the same philosophy. Both approaches are staring form the requirement for making decisions and support to decision-making ending with a diagnosis.

In the ex-ante approach, the goal optimising process is part of generating the schedule and the optimising of schedule to be released. This part is the core of the VALUEPOLE tool. The diagnosis in this approach is fixing the KPIs for generating the schedule and changing the parameter (knowledge gain by the ex-post approach) setting, if needed.

In the ex-post approach, the goal optimising process is based on the transaction within the schedule and the user interaction with the planning and control system, which is tracked and traced from the OLAP data warehouse system. Hence, based on this information the PIP-tool can link the schedule transaction and executed transaction results with the user interaction with the transaction and the mater data (parameters) the execution is based on.

The VALUEPOLE PIP approach uses a modified version of the deming plan-do-check-act cycle: diagnose, do check, act (DDCA).

Diagnose:
The input for the improvement activity is a diagnosis of the KPI(s), presented for the given result area, used to either confirm or change in current policy, business process, planning and control parameters or program directions, to meet these KPIs and sharing results of performance and changes conducted in pursuing these KPIs by the improvement activities.

Do:
Implement changes to key business process, often on a small scale if possible, to test possible effects. It is important to collect data for charting and diagnoses for the following 'check' step.

Check:
Measure the change process and compare the results (collected in 'do' above) against the expected results (targets or goals from the 'diagnoses') to ascertain any differences. Charting data can make this much easier to see trends in order to convert the collected data into information. Information is what you need for the next step 'act'.

Act: Diagnoses (analyze the differences to determine their cause)
Each will be part of either one or more of the DDCA steps. Determine where to apply changes that will include improvement. When a pass through these four steps does not result in the need to improve, refine the scope to which DDCA is applied until there is a diagnosis that involves improvement.

Through the work with both the participating SMEs and other field experience, these analyses were condensed into four distinct dimensions of analyses for implementation:

- order size statistics
- demand statistics
- delivery performance
- order book status.

Validation of the VALUEPOLE PIP module at Morsoe indicated that:

- inventory had increased by 79 % over a five year period, based on registrations of raw materials, work-in-progress and finished goods in their ERP-system;
- delivery precision to customers is quite low, based on an on-time-in-full comparison of registered (promised?) delivery dates / volumes and actual delivery notes in their ERP-system.

It has been demonstrated that the inventory level for finished goods can be almost halved while still improving on-time-delivery performance.

4) A NPDP portfolio model and optimiser

The fourth result from VALUEPOLE is a NPDP portfolio model and optimiser which enables the user to monitor via a rich user interface in VALUEPOLE the performance indicators for the portfolio of NPDPs within the enterprise.

In order to survive in the fast changing and competitive global economy, a company should be agile and respond quickly to the demands of the market. This requires redesigning products and developing new products constantly. Usually companies work in a multi-project environment in which there are a number of new product development projects. In this environment it is important to make a fast decision with regards to when and which of them to execute. Choosing the right project portfolio requires checking the availability of resources under a given set of constraints with various sources of knowledge. In that context we developed a project portfolio evaluation method including expert's knowledge including a workflow for product design and redesign suitable for optimisation and implementation in SMEs.

Having many potential new product development projects, it is difficult to plan their execution and schedule all of the operations. This is particularly the case for SMEs who operate on an engineer-to-order basis where each sales order requires a significant effort on redesign or new design. Sometimes companies have to decide to postpone execution of some tasks or even projects leading to sales orders. However, it is difficult to decide: which should be postponed, which are e.g. too expensive to produce, for which are the company lacking resources and so on. Therefore it is necessary to answer several questions: can a project portfolio be executed within determined deadlines at a set cost, under conditions of constrained availability of shared resources? Are there alternative solution variants for the execution of a group of projects? If so, which project portfolio variant is best, taking into account company specific evaluation criteria? Hence, often decisions are made subject to not only hard constraints such as; e.g. those related to capacity, but also soft constraints such as; e.g. cost or other political constraints. To answer these questions we must also define the measures of evaluation.

In the VALUEPOLE project we developed evaluation methods described in detail in deliverable 6.1. The evaluations of are based on:

ot - schedule execution deadline evaluation;
ow - resources use evaluation;
ok - schedule execution cost evaluation; and
op - project schedule overall evaluation.

These criteria can subsequently be used for multi-criteria evaluation of a NPD project portfolio. To solve the problem of project scheduling and evaluation in companies, we propose the project portfolio evaluation method using expert's knowledge.

On the basis of experience and practical knowledge, an expert evaluates the new product development project executions from the point of view of their utility (e.g. deadline, process execution cost, and resource charge) in the existing conditions and constraints, by means of verbal expressions; e.g. 'good', 'satisfactory', 'useful' as appropriate. Such evaluations are used in fuzzy modelling techniques including formal expressions which allow expressing unquantified human preferences as numerical values. Due to the fuzzy character of the presented information, rules of the 'if-then' type can be applied in their formal recording. Interdependencies in the evaluation system are established on the basis of the expert's knowledge. The knowledge is presented as facts, which complement the knowledge base as conditional rules.

The presented method can be implemented using constraint programming techniques. Two major features of constraint programming are expressivity and flexibility. Using a constraint programming framework, it is possible to describe very complex problems in a natural way. In constraint programming, constraints are exploited to reduce the amount of computation needed to solve the problem. The most important issues that contribute to the efficiency of constraint programming techniques are the procedures for a feasible solution selection (constraints propagation, variable distribution) and search strategies. In general, constraint propagation reduces the combinatorial size of the search space. Thus using constraint programming for the purpose of portfolio selection should enable on-line evaluation. The constraint propagation engine carries all the constraints during the search process. It computes the consequence of each decision taken by the search procedure or the user, tries to find inconsistencies as soon as possible and reduce the number of alternatives to be considered during the search. Constraint programming enables quick evaluation of whether or not a solution to the problem exists.

The proposed fuzzy multi-criteria evaluation of project portfolio will facilitate an automatic up to date project portfolio evaluation and decision making. Moreover, it will save time, reduce the production programs preparation cost, guarantee a flexible project portfolio execution and optimise production process in the context of extremising the criterion or criteria most important for the company.

The VALUEPOLE NPDP module delivers a structure for completely new product development projects and for redesigned product. New product development and redesign projects requires re-planning and re-scheduling operations in project-driven companies, therefore a fuzzy multi-criteria evaluation method to help companies in making decisions in this environment is presented. The subjective utility evaluation facilitates qualitative evaluation of the schedule obtaining a final solution, while taking into account the company individual features. The NPDP was also developed in the system based on constraint programming techniques. The fuzzy logic approach required 'qualitative' assessment by SMEs. The CSP method was based on quantitative performance to selected KPIs. The CSP method, based on quantitative performance to selected KPIs was the preferred solution for the SMEs as it mirrored the methodology developed in WP5 for PIP selection.

The four main project results are accessible to the SMEs end-users via the VALUEPOLE tool. VALUEPOLE consists of three modules: an enterprise modeller, an optimiser and a performance manager.

(i) The end-user interacts with the enterprise modeller module to tell the system the, who, what, when, where and how their products are made i.e. describes the entities in the organisation at enterprise level relevant to the main KPI. To make this task easier, we've implemented a workflow editor. This tool allows the user to denote the states in a process flow and define the relationships between them. Alternative routes are catered for using split and join constructs - (also referred to as branch and merge). The data for the supply-demand position is extracted real-time from the SMEs ERP system and / or databases such as spreadsheets.

A key feature of the modeller is that it is intuitive to use. Decision makers in small firms would not usually have the modelling expertise required to run advanced simulation-like tools. Using the VALUEPOLE tool, decision makers can model their firm, trying out multiple 'what-if' scenarios before committing to a decision.

(ii) Using this information the optimiser make's informed choices on how best to make the product to meet the constraints of the firm and the customer demand. The optimisation module then plans multiple resources using the KPI as the objective function. The advantage of using a hybrid metric such as sales revenue OTIF is that it provides a common language for both the decision maker and the mathematical optimisation functions. The optimisation algoithms developed for the VALUEPOLE tool optimise multiple resources versus multiple KPIs.

A key feature of the optimiser is the speed of the solution. The optimiser can produce solutions in near to real-time (minutes) for a typical engineer-to-order small firm. This is imperative if the decision maker is to interact with the tool, using his/her intuitive capability to generate alternate scenarios / models.

(iii) The performance manager module shows the decision maker what is the best possible outcome for the firm given the inputs from the enterprise modeller. For example, it will show the decision maker the predicted Sales Revenue that will ship on-time-in-full in any given time period (e.g. week) over any time horizon (e.g. quarter, year). This ex-ante prediction of sales revenue OTIF is based on optimisation algorithms for the current order books, (actual and forecasts), as well as the state of all resources within the firm. The decision maker is presented with diagnostic screens to rapidly identify which resources, entities and processes within the firm are constraining the firm from achieving sales revenue OTIF within the future planning horizon. This allows the decision maker to make improved decisions, typically on the allocation of resources, today that will affect future sales revenue OTIF. The decision maker is also given diagnostics of where the opportunities for improvement lie within the firm for organisational performance improvement. This allows the decision maker to prioritise improvement projects that will directly affect the KPI. The decision maker can also make decisions on new products based on the affect that the project will have on the Sales Revenue position of the firm given all the existing commitments of the firm.

A key feature of the performance manager is in the visualisation of the solution. The performance management tool has multiple 'drill down' features so that the decision maker can view the performance of each entity in the model and how it affects the overall performance of the firm.

Potential impact:

The VALUEPOLE project has delivered an ICT tool and a methodology for SME decision makers to maximise their competitive position with the minimum investment of resources, described above. VALUEPOLE supports organisations for improvements in processes and innovations in products based on either existing or new technologies.

An important knowledge outcome from the VALUEPOLE project for European SMEs, and indeed all enterprises, is that it is essential to have a structured decision making approach to the achievement of a suite of performance outcomes. A key finding of the VALUEPOLE project is that current information management with manufacturing SMEs is too fragmented to support such efficient decision making. Current approaches within small firms are mainly focused on recording past transactional events rather than support a more proactive predictive view of the future performance opportunities. The manufacturing SMEs within the VALUEPOLE project have demonstrated that they can not only survive the current economically challenging period but have thrived against worldwide competition. Indeed, the market performance of these firms during the period of the VALUEPOLE provides good evidence that manufacturing SMEs within the EU have ample opportunity to exist and provide good careers if they are enabled with the appropriate performance management models, ICT tools and methodology.

The SME manufacturing demonstrators in the consortium have continued to thrive throughout the period of this project, despite the tough economic climate currently for SME manufacturers. Specifically, with the assistance of the VALUEPOLE project, the Irish SME Burnside has doubled its employed and tripled sales (+200 % sales) in export markets. SME Millhouse has doubled sales and won back business for the UK that had been previously subcontracted to China. The SME end-users report that they have exceeded benefits of greater than 5 % of revenue.

VALUEPOLE has the potential to deliver similar success of other European manufacturing SMEs using the VALUEPOLE demonstrators as validation. VALUEPOLE can demonstrably help SMEs to manage their enterprise performance prediction and diagnostics to attain their operational, tactical and strategic objectives. At an operational level of enterprise decision making, VALUEPOLE enables a focus on the short term performance of the firm typically from today to the next 60 days. This short time horizon is focused on immediate sales order execution. The shipping customer sales orders on hand is essential to ensuring the revenue performance of the firm. At the tactical level of enterprise decision making, VALUEPOLE enables a focus on the medium term performance improvement of the firm typically from 60 to the next 250 days. This short to medium term time horizon, is typically focused on immediate demand enhancement (building the best sales order book), large sales order execution. VALUEPOLE models both the KPI response and the execution of PIPs that connect to increased market demand (both volume and/or profit margin). The VALUEPOLE connects PIPs to cost reduction where process improvements are planned with the firms workflows. At the strategic level of enterprise decision making VALUEPOLE enables a focus on the medium to longer term performance improvement of the firm typically, from 250 days to the next 5 years. In this medium to long term time horizon, focus on immediate demand enhancement (building the best order book), large scale market development initiatives. VALUEPOLE models both the KPI response and the execution of a portfolio of new product development projects that connect to increased market demand (both volume and/or profit margin) and the expected economic contribution of new capital equipment investments.

The VALUEPOLE results will be commercialised by the SME partner ManOPT Systems Ltd., in their new-to-market flagship product: MAKE. (see http://www.manopt.com online). ManOPT have reported that, one month post project closure, sales prospects are likely to exceed the original year 1 sales targets defined in the description of work. The market feedback on the VALUEPOLE tool prototype is that there a definite need for the VALUEPOLE tool in manufacturing companies of all sizes. The tool has been presented to over 300 companies at four public dissemination events. Over 25 in company presentations have been delivered in the last 3 months. The market feedback is extremely positive. So far, only one company has decided not to proceed to a sale. The company management in this family owned-managed company has agreed that there is a potential to increase their revenues by at least ten per cent but they do not want to change from their steady state annual production plans. This is of major concern to the employees and next generation management who fear that such an approach will loose the company market share and ultimately their jobs. ManOPT expects to grow the number employed from current 10 to nearly 100 within 3 years.

ManOPT would not have had the expertise inhouse to develop a tool such as VALUEPOLE without firstly the cooperation of the pan-European research community. Secondly, the validation of the concepts in real SMEs across the EU has ensured that the tool meets the needs of SMEs.

The scientific concepts have been presented to over 1000 people in the technical and scientific community at major international conferences (13 journal papers, 34 conference papers, 2 PhD dissertations and 6 BSc / MSc dissertations). The scientific community is excited about the concept of real time performance prediction combining both optimisation and simulation.


Project website: http://www.valuepole.eu