Assessing the Status of a Roadmap: When is the …...status of the roadmap. But, to determine when...

Assessing the Status of a Roadmap: When is the Time to Review?

Ronald Vatananan, Nathasit Gerdsri College of Management, Mahidol University, Bangkok, Thailand

Abstract--Maintaining a roadmap is a crucial part for any

organization that wants to keep the roadmapping process alive after its development. However, it is not easy to maintain and review a roadmap, because an organization is exposed to constant changes in its business environment. An organization has to review its roadmap to include the changes that have a significant affect on the status of the roadmap. But, to determine when it is time to review a roadmap is a major challenge for any organization. As a result, most organizations maintain a roadmap on a predetermined regular basis. This paper proposes an analytical approach and evaluation model to determine the status of a roadmap. The proposed approach will assist an organization to decide when a review of its roadmap is necessary. A case example is presented to demonstrate the computational process and applicability of the proposed approach.

I. INTRODUCTION

Technology roadmapping (TRM) has gained acceptance

among practitioners as a tool to bridge the requirements from the business environment of an organization with their capabilities [1-5]. However, as a fairly new concept the roadmapping technique faces some challenges in its implementation and operationalization [6]. Keeping a roadmapping process alive, after its implementation in an organization seems to be a major challenge for many organizations [4, 6-10]. One way to ensure the sustainability of a roadmap is to integrate the process into the ongoing operations of an organization [4, 11-13]. Although an organization is able to effectively integrate a roadmapping process, maintaining and reviewing the process is still difficult [6, 11, 14-17]. Determining the need to review the roadmapping process is a major problem and most firms result to a predetermined maintenance and update schedule [11, 13]. The drawback with this review technique is that changes in the organization’s business environment often occur at random and with different effects on a roadmap. Once a roadmap is developed, it is exposed to the constant changes of the business environment. Therefore, organizations that use roadmapping as a planning tool have to keep their roadmap up-to-date by incorporating changes that can influences their strategy. To schedule a maintenance of their roadmap, an organization faces the challenge of determining whether the changes in their business environment have become severe enough to justify a review.

Academics and practitioners have acknowledged the importance of maintaining a roadmapping process to reflect changes in an organization’s business environment [13, 14, 16]. Nevertheless, how to monitor such changes or when and how to review a roadmap remains a challenge to the TRM community. This paper proposes an analytical approach that determines when a roadmap needs to be reviewed. The analytical approach constructs an evaluation model that

determines the status of a roadmap. The evaluation model will enable an organization to assess the status of its roadmap by monitoring and analyzing changes in the key drivers that influence the organization’s strategy. In this study, the case example of a marketplace business for food products is presented to demonstrate the application and operation of the proposed approach.

II. A LITERATURE REVIEW ON TRM IMPLEMENTATION AND OPERATIONALIZATION

In the competitive business environment of today, it is

vital to develop a strategic plan that can link the various business activities of an organization [18]. The challenge for many organizations is to identify their core capabilities and allocate available resources into the right technologies and innovations [19-21]. Numerous organizations have turned to technology roadmapping (TRM), to assist the development of their strategic or technology plan. Roadmapping is a technique that links the requirements of an organization’s business environment with their capabilities [2, 3, 8, 21-24]. Initially, product technology roadmaps were used as a means to link the technological capabilities of a firm with the market requirements [20, 22, 25].

A generally accepted format for a roadmap is a two-dimensional diagram that represents its components on the vertical axis and a timeframe on the horizontal axis [6]. The vertical axis of a roadmap consists of several layers and sub-layers, which can be designed to meet the particular needs associated with the roadmapping activity [26]. The horizontal aspect represents the time frame of a roadmap that reflects the evolution and anticipated changes of drivers and technologies.

The roadmap development is facilitated through a workshop oriented process [27] that involves cross-functional teams with individuals from different levels of an organization [15, 28]. Developing a roadmap is an iterative process where the focus and details increase with each iteration [8-10]. To date, various roadmapping processes have been implemented, which reflect the flexibility of the TRM technique. For example, roadmapping has been applied in product & service development [2, 9, 11, 20], innovation and knowledge creation [6, 7, 29-33], project planning [34-37], technology planning [1, 38] and policy planning [39, 40].

The approach for implementing roadmapping in an organization can be classified into three stages: initiation, development, and integration [6, 11]. Organizations that intend to develop a roadmap as a one-time effort to guiding their strategic vision stop the TRM implementation after

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2013 Proceedings of PICMET '13: Technology Management for Emerging Technologies.

completing the development stage [16]. However, organizations who intend to assimilate the TRM process into their ongoing business operations, need to continue with the integration stage. Integrating a roadmapping process is vital to keep the roadmap alive. Therefore, the TRM process should not be considered as a one-time effort and needs to be exercised as an ongoing process [15].

Many organizations acknowledge that it is a major challenge to sustain roadmapping as an ongoing process [4, 6-10]. To address this challenge researchers and practitioners have focused their efforts on integrating [11-13] and operationalizing the process [41-49] as one of the organization’s ongoing business activities. At present, the roadmapping community is actively engaged in the operationalization of the roadmapping process by standardizing the implementation process [14, 15, 30, 50, 51] and by developing tools that automatize the roadmap operation [41, 42, 44, 52-55]. However, existing research and literature center their attention mainly on the development of technology analysis tools to support the capability layer of a roadmap [15, 41, 44, 53, 54, 56-59].

The maintenance of a roadmap is treated as an important part to keep a roadmapping process alive after its development [13, 14, 16]. But, maintaining and reviewing a TRM process to reflect changes in an organization’s business environment is difficult [6, 11, 14-17]. This is why most firms result to periodical maintenance and update schedules [11]. The analytical approach and evaluation model proposed in this paper offers a solution to this problem by operationalizing the TRM maintenance process.

III. ANALYTICAL APPROACH AND MODEL DEVELOPMENT

A. The Analytical Approach

In this study the analytical approach shown in Figure 1 is proposed to enable an organization to know when a roadmap needs to be reviewed. An organization can integrate the approach into the roadmap implementation process or execute it as an independent process in case that the organization already developed a roadmap. The analytical approach provides the foundation to develop an evaluation model that determines the current state of an organization’s roadmap. The purpose of the evaluation model is to determine the level of impact from changes in the business environment of an organization. To determine the level of impact, the evaluation model monitors changes in the key drivers indicated on a roadmap and analyzes the degree of impact from these changes. Once constructed, the evaluation model evaluates the impact of changes on key drivers of a roadmap and produces a TRM status signal. The TRM status signal is then used as an indicator for the status of the roadmap. Based on the value of the TRM status signal, a recommendation is offered to maintain, adjust or revise a roadmap.

With the help of the analytical approach, organizations are able to incorporate the changes of their business environment into their roadmap. As a result, an organization can ensure the accuracy of its technology and strategic plan, which supports the sustainability of the roadmapping process as a vital and integral part of an organization’s business activities. The construction of an evaluation model involves the contributions from experts at a management level, whereas the operation of the model takes place at the operational level. Constructing the model is a top-down process, where as the systematic process of operating the evaluation model is an iterative bottom-up process.

Fig. 1. Analytical Approach

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B. Development of the Evaluation Model The evaluation model consists of a simple hierarchal

structure (Figure 2), where each criterion is assessed with respect to the model’s objective and a mathematical model to calculate the TRM status signal STRM as presented in Equation 1. The hierarchy of the roadmap’s evaluation model consists of three levels and is constructed by a management team of an organization. Level 1 defines the model’s objective, which is represented by the roadmap status signal (STRM). Level 2 identifies a set of key drivers (KDi) and their relative importance (wi) with respect to the model’s objective. Level 3 identifies the measurable sub-drivers (SDij) and determines their relative importance (wij) associated with each key driver (KDi). To analyze the impact from changes, experts have to determine a unit of measurement (mij), the baseline value (mbase) and a data source for each sub-driver (SDij). The last step on level 3 is to define the tolerance limits (t2➞1, t1➞0, t0➞1 and t1➞2) that are used to determine the level of impact from changes in the key drivers.

The objective of the evaluation model is to determine how much the impact of changes in key drivers affects a roadmap presenting the strategic goals of an organization in each time period. The roadmap status signal (STRM) produced by the model provides management with a gauge of the roadmap’s current state. The value of the TRM status signal (STRM) represents the collective level of impact x(mij) from any change in all sub-drivers. The STRM signal is calculated using

Equation 1 and produces a value that falls in the range of [0, 2] = {STRM ∈ R ⎮ 0 ≤ STRM ≤ 2} [17].

Equation (1) where: wi : Relative importance of key driver (i) with respect to the

objective. wij : Relative importance of sub-driver (j) associated with

key driver (i). mij : Measurement value of sub-driver (j) associated with key

driver (i). x(mij) : A signal representing an integer value x(mij) = [0, 1,

2] to indicate the level of impact from a change in the measurement value mij on a roadmap for the sub-driver (j) under key driver (i).

if x(mij) = 0: Changes in mij have no impact or little but not significant impact.

x(mij) = 1: Changes in mij have a moderate impact x(mij) = 2: Changes in mij have a major impact

: A collective signal (SKDi) indicating the status of measurement values for all sub-criteria j (i.e. sub-driver (SDj)) under the criterion i (i.e. key driver (KDi)).

: A collective signal indicating the overall status of a roadmap.

STRM : TRM Status signal

Fig.2. Generic Example for a Evaluation model hierarchy.

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The STRM signal consists of three intervals that provide an indication of a roadmap’s current status and also represents different recommendations for a roadmap review (Figure 3). Depending on its value, the STRM signal issues a recommendation to either maintain, adjust or revise a roadmap. The experts of a company are responsible for defining the three intervals, by determining how much change in the key drivers of the roadmap is acceptable to the organization. Figure 3 shows a generic example that uses the cut-off values T1 and T2 to separate the intervals of the STRM signal into three equal parts. Any value in the range of STRM = [0.00, T1) returns a green signal, recommending to maintain the roadmap as is. Should the value of the status signal fall between STRM = [T1, T2] a yellow signal is issued indicating a moderate impact from a change in the roadmap’s key drivers and recommends an adjustment of the roadmap. A red signal is given for a STRM value in the range of STRM = (T2, 2.00], recommending a major revision of the roadmap. However, it is up to the management to determine the size of the intervals by adjusting the cut-off values of T1 and T2. For example, if the STRM signal is separated into three equal intervals, then the cut-off values are defined as T1 = 0.67 and T2 = 1.33. Therefore, the intervals of STRM are defined as, STRM = [0.00, 0.67) issuing a maintain recommendation, STRM = [0.67, 1.34] providing an adjust recommendation and STRM = (1.33, 2.00] recommending to revise the roadmap. However, if an organization wants the evaluation to be more sensitive towards changes in the key drivers, then the experts can reduce the the size of the intervals. For example, lowering the cut-off value of T1 from 0.67 to 0.33, will decrease the range of STRM values that can return a green signal and the evaluation model becomes more sensitive towards any change in the key drivers.

Fig. 3. Generic STRM Signal

C. Operationalization of the Evaluation Model

The experts determine the key drivers (KDi) of the roadmap and assign a relative importance (wi) to each driver. Key drivers are determined at a conceptual level, since an organization may not be able to measure some of the key drivers directly. Their relative importance to an organization’s roadmap is assessed with respect to the objective of the model. To assess the impact of a change in the key drivers an organization needs to analyze changes in the respective sub-drivers. Equation 2 calculates the SKDi

indicator that shows the accumulated affect of all sub-drivers (SDij) with respect to a specific key driver (KDi). Similar to STRM, the key driver indicator SKDi consists of three intervals that are determined by the cut-off values t1 and t2. The SKDi indicator as well takes on a value in the range of [0, 2] = {SKDi ∈ R ⎮ 0 ≤ SKDi ≤ 2}, where SKDi = [0.00, t1) results in a green signal, SKDi = [t1, t2] in a yellow signal and SKDi = (t2, 2.00] in a red signal. Providing an additional signal at this level allows experts to locate which changes have what kind of impact on the roadmap.

Equation (2) After determining key drivers, the experts identify their

respective sub-drivers (SDij) and their relative importance (wij) for each KDi. Then a unit of measurement (mij) is determined for each SDij, together with a data source to support the measurement. A baseline value (mbase) for each of the sub-driver measurements is recorded to represent the status quo of the evaluation model.To operationalize this analysis, the experts have to define proper tolerance limits. The tolerance limits (t2➞1, t1➞0, t0➞1 and t1➞2) define five tolerance intervals of mij that correspond to a level of impact x(mij) according to the deviations from mbase as shown in Figure 4. Any deviation from mbase automatically receives an integer value x(mij) = [0, 1, 2], to represent the level of impact from changes on a sub-driver (Equation 3).

Equation (3) It is difficult for experts to directly define the tolerance

limits that can determine the level of impact from any change that causes a deviation from the baseline value of a sub-drivers. To develop proper tolerance limits, the experts can follow 3 steps:

Step one: Develop a perception curve representing the degree of impact from a change that deviates from the mbase value. To derive the curve, experts are asked to assign a degree of impact to a range of mij values. The degree of impact represents the expert’s perception on how much a deviation in mbase affects an organization’s roadmap. The example in Table 1 shows a range of possible mij values to which the experts have assigned their perception on the degree of impact regarding the deviations from mbase. The degree of impact can range from 0 ‘no impact’ up to 100 ‘severe impact’. In Table 1 the baseline value is defined as mbase = 100, which is equivalent to a degree of impact value of 0, because mbase represents the status quo at the time of the evaluation model development. Table 1 also shows that the more the mij values deviate from mbase, the higher the degree of impact as perceived by the experts. A scatter plot is then constructed from the values in Table 1, representing the various deviations from mij and their degree of impact. The best-fit line derived from the scatter plot represents the perception curve in Figure 4.

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TABLE 1. DEGREE OF IMPACT BASED ON DEVIATIONS OF mij FROM mbase

mbase mij: 0 25 50 75 100 125 150 175 200

Degree of Impact: 100 60 30 5 0 5 30 60 100

0 = no impact, 100 = severe impact

Step two: Experts determine the cut-off values for the degree of impact from changes in the sub-driver. This is done by defining how much mij is allowed to deviate from mbase before a yellow or red signal is issued. The size of the degree of impact intervals depends on the experts and their perception on how much a change in the sub-driver is acceptable. For example, if the management perceives that the impact from changes in key drivers are equally important to the status of a roadmap, then the cut-off values for the degree of impact intervals are 33 and 67 (Figure 4). The two cut-off values define the three intervals used to calculate the tolerance limits of the sub-driver measurement.

Step three: Calculate the tolerance limits based on the perception curve, using the cut-off points obtained in step two. Therefore, the tolerance limits for the sub-driver measurement in Figure 4 are defined as t1➞0 and t0➞1 for the degree of impact of 33, and t2➞1 and t1➞2 for the degree of impact of 67.

The tolerance limits define the tolerance intervals used for the analysis. According to Equation 3 a green signal is given for x(mij) = 0 of any mij value that falls into the tolerance interval of [t1➞0, t0➞1]. A yellow signal is issued for x(mij) = 1 for any mij value in the tolerance interval of [t2➞1, t1➞0) and (t0➞1, t1➞2], and a red signal is given for x(mij) = 2 for mij values that fall into the tolerance interval of [∞, t2➞1) and (t1➞2, ∞]. To reflect an organization’s sensitivity towards changes in the sub-drivers, the experts can adjust the size of the tolerance limits by changing the cut-off values for the degree of impact intervals. For instance, reducing the degree of impact interval that would result in a green signal from [0, 33] to [0, 20], will make the analysis of changes on any sub-driver deviating from the mbase value more sensitive.

The evaluation model is now ready to determine the level of impact on the status of a roadmap for any change in the sub-driver measurements. To do so, an organization monitors the sub-drivers of the evaluation model for any changes in mbase. Once a change occurs the tolerance intervals determine the level of impact for the deviation from mbase and an integer value is issued for x(mij) using Equation 3, which is then used to calculate STRM with Equation 1.

IV. COMPUTATIONAL DEMONSTRATION: A CASE EXAMPLE

A. Background of the Case Example

In the case example the evaluation model is applied to a strategic roadmap of a marketplace business for food products. The marketplace complex has served as a center for the local community to sell and buy fresh produce for over 40 years. Even though, the management of the complex is not directly responsible for the operations of individual vendors, customers and government hold them accountable for any problems within the premis of the complex. The emergence of hypermarkets in the area has drawn many customers away from the local market place and the loss in business has led many vendors to drop their quality and standards. To adress this issue the management of the complex has recently decided to raise the image of the business by upgrading its facilities and operations to achieve above average “Clean & Green” standards by 2020. B. The Strategic Roadmap of a Marketplace Business

The roadmap introduced in this case example (Figure 5) presents a strategic roadmap for the business of a marketplace complex, which has the objective to become “Clean & Green” by the year 2020.

Fig. 4. Generic Patter of a perception curve for a Sub-Driver Measurement

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Fig. 5. Strategic Roadmap for a marketplace complex to become “Clean & Green” by 2020

The management of the complex has decided to pursue

four strategic goals in order to achieve their objective within 2020. Figure 5 shows that at present the complex is working on the strategic goal to provide clean facilities by 2012. For the short-term, the strategic roadmap focuses on the goal to ensure and sustain food safety by 2015. In the medium-term the focus will shift to achieving zero landfill by 2018 and for the long-term the roadmap concentrates on switching to 100% sustainable energy by 2020. The following describes how the strategic goals can be achieved, by focusing on necessary developments, technologies and innovations.

Providing Clean Facilities: Figure 6 shows the current goal for 2012, which aims to provide clean facilities for customers and vendors throughout the complex by 2012. To achieve this goal, the complex needs to deploy several projects and activities, such as proper facility management and necessary renovations. For the proper facility

management the decision makers have decided to outsource major cleaning tasks and pest control to professional firms. Facilities of the complex will undergo renovations to maintain a healthy and safe environment. Options of self cleaning, anti fungi concrete and tiles are under advisement to provide easier to clean surfaces.

Ensure & Sustain Food Safety: The short-term goal presented in Figure 7 intends to implement and enforce above average food safety standards by 2015. The implementation of a food safety management system that is supported with pathogen detection technology will assist management to monitor and enforce food safety standards. The food safety management system will also include mandatory food safety training and regular food safety inspections. The food safety training courses and inspections are intended to improve the awareness and preparedness of vendors towards food safety.

Fig. 6. Current Strategic Goal of “Providing Clean Facilities” Fig. 7. Short-Term Strategic Goal to “Ensure & Sustain Food Safety”

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C. Development of the Evaluation Model For the purpose of a computational demonstration, the

objective of the evaluation model is to determine the current state of the company’s roadmap aiming at the short-term goal as shown in Figure 7. Three key drivers, Health Concerns, Healthy Lifestyle and Government Policies, are considered to have a direct influence on achieving the short-term goal to Ensure & Sustain Food Safety throughout the complex. Table 2 list the key drivers (KDi) that management considers to have a significant affect on the short-term goal, together with their relative importance (wi).

As Table 2 shows, the management considers government policies (KD3) as the most influential key driver with a relative importance of w3 = 0.45. Health concerns (KD1) has been identified as the next most influential key driver with a relative importance of w1 = 0.35 followed by healthy lifestyle with w2 = 0.20.

After the management has determined the criteria on the second level of the hierarchical model, they continue with defining the sub-drivers for each of the key driver. For this

case, nine different sub-drivers are identified in Table 3, to measure changes in the three key drivers from Table 2.

D. Computational Demonstration of the Evaluation Model

Figure 8 shows the evaluation model hierarchy of the strategic roadmap, to visually present the condition of the roadmap on different levels. Level one of the hierarchy shows the assessment result for the current state of the strategic roadmap in achieving the short-term goal. Level two measures changes in the key drivers by monitoring and recording changes in their respective sub-drivers on level three. Once developed, all indicators of the evaluation model in Figure 8 are green, to represent the status quo. At this time there are no changes affecting the status of the roadmap and therefore the level of impact from a change in the mbase is x(mij) = 0. The evaluation model has to be able to absorb minor changes in the business environment of the organization and issues an alert signal for only those changes that will affect the status of the roadmap.

TABLE 2

KEY DRIVERS THAT INFLUENCE THE ROADMAP’S SHORT-TERM GOALS

KDi Key Drivers Relative Importance (wi)

KD1 Health Concerns 0.35

KD2 Healthy Lifestyle 0.20

KD3 Government Policies 0.45

TABLE 3 SUB-DRIVERS (SDIJ) FOR EACH KEY DRIVER (KD1)

KD1: Health Concerns SD1j Sub-Driver Details w1j

SD11 No. of reported cases of food poisoning 0.10 SD12 No. of reported cases of infectious diseases 0.10 SD13 Customer complaints 0.50 SD14 Market Food Safety Inspection 0.30

KD2: Healthy Lifestyle SD2j Sub-Driver Details w2j

SD21 % of population exercising 0.4 SD22 % Obesity (age 20+), 2008 0.4 SD23 % of population smoking 0.1 SD24 Per capita (age 15+) consumption of pure alcohol in liter per year 0.1

KD3: Government Policies SD3j Sub-Driver Details w3j

SD31 Food Safety standards 1.00

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Fig. 8. Evaluation Model Hierarchy

For example, as time passes the management detects some

changes in the sub-drivers SD11, SD12 and SD13 of key driver KD1. The baseline value of the three sub-drivers have deviated from mbase = 100 to m11 = 150 for SD11, mbase = 100 to m12 = 250 for SD12 and mbase = 0 to m13 = 2 for SD13. Once management has recorded the deviations in these sub-drivers, the evaluation model determines the level of impact from that change by using Equation 3. After the level of impact is calculated, the evaluation model issues revised signals for the changes in the three sub-drivers. A yellow signal is given for the level of impact from a change in SD11 of x(mij) = 1 and green signals are issued for SD12 and SD13 with x(mij) = 0. Table 4 summarizes the changes in KD1 and details how a deviation in mbase determines the level of impact from that change. The tolerance limits recorded in Table 4 show how the new measurement m11 = 150 of SD11 falls into the tolerance interval of (123, 158], which is equivalent to a level of impact value of x(m11) = 1. The new measurement values of m12 = 250 and m13 = 2 for SD12 and SD13 remain within their green tolerance intervals of [t1-0, t0-1] and therefore return a respective impact values of x(m12) = 0 and x(m13) = 0. The level of impact values (x(mij)) returned by the evaluation model show that the change in SD11 has a mediocre impact on the status of the KD1, as is reflected by the yellow signal issued. The changes in SD12 and SD13 return a green signal each and show that they are not

significant enough the have an affect on the key driver indicator SKD1. The key driver indicator (SKD1) that is calculated using Equation 2 remains green, even though SD11 shows a yellow signal for the change in its baseline value. In this example, the management has decided to use equal intervals for all the indicators of the evaluation model. Using Equation 1 a new roadmap status signal of STRM = 0.05 is calculated, which falls into the maintain (green) interval of STRM = [0, 0.67]. This shows that the level of impact from changes in the sub-drivers of KD1 have no significant impact on the status of the roadmap and that the evaluation model is able to absorb some changes in its key drivers.

E. Scenario Analysis

The following section shows two scenarios, where a change in the key drivers leads to a different STRM signal. Scenario A shows how a minor shift in a few sub-drivers leads to a yellow signal of the STRM signal, recommending an adjustment of the roadmap. Scenario B demonstrates how major changes in two of the most influential sub-drivers lead to a red signal suggesting a revision of the roadmap.

Scenario A: The STRM signal turns from green to yellow, indicating a mediocre impact of changes in the business environment and recommending an adjustment of the roadmap.

TABLE 4

KD1: HEALTH CONCERNS

SD1j Description w1j Tolerance Limits

m1j x(m1j) w1j * x(m1j)t2➞1, t1➞0 mbase t0➞1, t1➞2

SD11 No. of reported cases of Food Poisoning 0.15 5 26 100 122 158 150 1 0.15 SD12 No. of reported cases of infectious diseases 0.15 44 108 200 262 313 250 0 0.00 SD13 Customer complaints 0.40 0 0 0 4 8 2 0 0.00 SD14 Market Food Safety Inspection 0.30 12 30 50 77 95 50 0 0.00

SKD1 = 0.15

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TABLE 5 KD1: HEALTH CONCERNS


m1j x(m1j) w1j * x(m1j)t2➞1 t1➞0 mbase t0➞1 t1➞2

SD11 No. of reported cases of Food Poisoning 0.15 5 26 100 122 158 150 1 0.15

SD12 No. of reported cases of infectious diseases 0.15 44 108 200 262 313 250 0 0.00

SD13 Customer complaints 0.40 0 0 0 4 8 5 1 0.40

SD14 Market Food Safety Inspection 0.30 12 30 50 77 95 28 1 0.30

SKD1 = 0.85 TABLE 6

KD3: GOVERNMENT POLICIES

SD3j Description w3j

Tolerance Limits m3j x(m3j) w3j * x(m3j)

t2➞1 t1➞0 mbase t0➞1 t1➞2

SD31 Government imposes Food Safety standards 1.00 0 1 2 1 1 1.00

SKD3 = 1.00

Scenario A shows how a sudden increase in reported cases

of food poisoning (SD11) has led to changes in other drivers and subsequently triggers an adjustment of the strategic roadmap for the business. After reported cases of food poisoning have risen from mbase = 100 to m11 = 150, the government decides to act by imposing stricter food safety regulations (SD31). After considering the new government policy on food safety, the management decides that the change has a mediocre impact on their roadmap and assigns an impact value of x(m31) = 1. A food safety inspection (SD14) is conducted by the management and vendors in the complex receive an average score of m14 = 28. The result from the inspection shows that food safety standards in the complex are below the baseline value of mbase = 50. With news and rumors about the recent food poisoning cases spreading, customers have become more sensitive and start to complain (SD13) about the lack of food safety standards in the complex. Including this rise of customer complaints to m13 = 5 into the calculation of the evaluation model yields a yellow signal for KD1 of SKD1 = 0.85. Table 5 and 6 calculate the SKDi values for KD1 and KD3 to show the level of impact that changes have on the strategic roadmap. The changes in mbase are recorded in the mij column of the table and x(mij) is determined with Equation (3). Including the relative importance of the sub-drivers a new SKDi value is calculated using Equation (2).

Since equal intervals are used throughout the evaluation model, a recommendation to adjust the roadmap is given when the TRM status signal falls into the range of STRM = [0.67, 1.34]. Using Equation (1) to calculate the impact from the changes in the sub-driver measurements, yields a new STRM value of 0.75 (Figure 9).

Scenario A has introduced several changes in the business environment of the marketplace complex causing an increase of the key driver indicators to SKD1 = 0.85 and SKD2 = 1.00. Figure 9 shows that the combined impact of these changes

rises the STRM value from 0.00 to 0.75, which falls into the yellow interval of [0.67, 1.34]. The yellow STRM value indicates that the changes of Scenario A are significant enough to provide a recommendation for an adjustment of the strategic roadmap. In this example, the experts would adjust the timing for their development of food safety training to be completed and ready at an earlier time.

Scenario B: The STRM signal turns from yellow to red, indicating that the changes in the business environment of the marketplace complex have a severe impact on the status of the strategic roadmap and recommends a revision.

Even though the government has improved regulations regarding food safety (SD31), cases of food poisoning (SD11) continue to rise and reach m11 = 200 cases per year. With public concerns over food safety issues at its peak, customer complaints (SD13) keep on increasing to m13 = 10 instances. The government reacts to this trend in public opinion by strictly enforcing the new set of regulations they previously issued through rigorous controls. The impact of these changes causes the STRM signal to turn red, indicating a severe affect on the strategic roadmap. Table 7 shows that the new sub-driver measurements m11 = 200 and m13 = 10 are larger than the t1-2 tolerance limit, leading to a new level of impact value of x(m11) = 2 and x(m13) = 2. The management also considers the new stance of the government towards the enforcement of food safety standards as a major shift and assigns an impact value of x(m31) = 2. Tables 7 and 8 summarize how the changes in KD1 and KD3 lead to new level of impact values that then raise the key driver indicators to SKD1 = 1.40 and SKD3 = 2.00.

Scenario B demonstrated how the situation from Scenario A continues to worsen. Even though the Healthy Lifestyle (KD2) of the population has not changed, the changes in KD1 and KD2 are significant enough to raise the STRM value from 0.75 to 1.39 (Figure 10).

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Fig. 9. Scenario A: The impact of changes causes STRM to issue an adjust recommendation.

TABLE 7

KD1: HEALTH CONCERNS


m1j x(m1j) w1j * x(m1j) t2➞1 t1➞0 mbase t0➞1 t1➞2

SD11 No. of reported cases of Food Poisoning 0.15 5 26 100 122 158 200 2 0.30

SD12 No. of reported cases of infectious diseases 0.15 44 108 200 262 313 250 0 0.00

SD13 Customer complaints 0.40 0 0 0 4 8 10 2 0.80

SD14 Market Food Safety Inspection 0.30 12 30 50 77 95 28 1 0.30

SKD1 = 1.40 TABLE 8

KD3: GOVERNMENT POLICIES


m3j x(m3j) w3j * x(m3j)t2➞1 t1➞0 mbase t0➞1 t1➞2

SD31 Government imposes Food Safety standards 1.00 0 1 2 2 2 2.00 SKD3 = 2.00

Fig. 10. Scenario B: The impact of changes causes STRM to issue a revise recommendation.

A red STRM signal indicates that the business environment

of the marketplace complex has changed significant enough to recommend a revision of the strategic roadmap. For example, a revision may include major adjustments of the strategic goals or a complete make-over of the roadmap. In this case example, the experts decided that the facility renovations have to be implemented earlier and their scope will be larger than expected, since the government requires the business to change from an open-air to a closed-door layout. To facilitate the implementation of higher food safety standards management has also decided to include a food safety awareness program into the development layer of their roadmap.

V. GENERALIZABILITY OF THE APPROACH AND EVALUATION MODEL

One of the strongest features of roadmapping is the ability

to customize the technique used in developing a roadmap to fit with different purposes. For example, some organizations

want to develop a roadmap to guide their product and technology development, while others may aim to develop a roadmap to guide their capability development, etc. In this study, the proposed analytical approach and evaluation model are designed to support this strength of the roadmapping technique. Organizations are able to apply the proposed approach to determine the status of a roadmap regardless of their objective, business or industry. The approach guides a management team of an implementing organization through the construction of the evaluation model, based on their individual objective and roadmap structure. The construction of the evaluation model depends on the model’s objective, criteria and the management’s tolerance towards changes.

For example, two companies operating a similar business may end up with a similar roadmap. So, the evaluation model of the two businesses may be similar in nature, but their perception on the tolerance limits for changes might greatly differ. One firm might be extremely risk averse and therefore defines the tolerance limits to be more sensitive towards changes in the key drivers of their roadmap. The

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other firm is a risk taker and defines their tolerance limits to be less sensitive towards changes. To reflect a change in the model’s objective, the experts can change the set of criteria and then follow the model development steps, by determining the relative importance of the new key and sub-drivers, as well as redefining the tolerance limits of their measurements.

VI. CONCLUSION

Organizations implementing the roadmapping process always face the challenge of keeping the process alive after its development. Even with a successful integration of the process into ongoing business activities, the implementing organizations still struggle with the maintenance of their roadmap. Maintaining a roadmap means to adjust or revise the content and timing of targets. To review their roadmap, an organization needs to form a cross-functional team of experts at a management level that can determine the necessity and extend of the adjustments or revisions. For most firms, forming such a cross-functional team includes major time and money consuming activities. As a result, organizations perform their roadmap reviews on a predefined schedule. However, the business environment of an organization is dynamic and changes in the key drivers can affect the state of a roadmap at any time. Under this circumstance, organizations are faced with the problem to determine when a review of their roadmap is actually necessary. The analytical approach and evaluation model proposed in this paper provides an organization with the means to monitor changes in their business environment and determines their effect on the status of a roadmap. The TRM status signal (STRM) that is produced by the evaluation model, issues a recommendation to the management team whether a roadmap needs to be maintained, adjusted or revised.

The analytical approach offers several benefits to the organization implementing a TRM process. With the application of the proposed approach, an organization would become more proactive with their roadmap maintenance, by determining when a review is actually necessary. The analytical approach is semi-automated, to minimize the problems that are produced by human judgment and bias. The evaluation model is flexible and can be customized to suit any objective and business. In addition, focusing only on the most important key drivers reduces the complexity of the evaluation model. With this simplicity, it enables an organization to adjust and integrate a roadmap review process as a part of their ongoing activities.

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