Digital Skill Transformation and Knowledge Management Challenge in a Global IT Service Firm An Empirical Study
Abstract. This paper aims to discover key performance indicators (KPIs) in°uencing digital skill transformation in global IT service ¯rms, reveal its unique features, and assert the e®ect of these KPIs on ¯rms' digital skill transformation and knowledge management initiatives. This research is mainly based on primary data. The researcher started data collection by conducting a Focused Group Discussion (FGD) with subject matter experts (SMEs), followed by in-depth personal interviews with the key organisational individuals. Then, a primary survey is carried out using a qualitative questionnaire across all the existing employees of the largest business unit of a global IT service ¯rm. Findings suggest that Total IT Expe- rience (EXP), Reading Time (RT), E®ective Mentoring (EM), and Training E®ectiveness (TE) primarily impact employees' digital skill transformation. Besides, the technical capability and understanding of existing employees' supervisors or managers directly correlate with the project environment, which in turn impact employees' e®ectiveness during their digital skill transformation journey.
1. Introduction
There is an ongoing interest across Indian global IT service organisations in how existing employees can be reskilled into digital technology areas (Data Science, AI/ ML, Cloud, etc.) and deployed e®ectively into competitive project environments. Knowledge management and skill-building process are directly related to project success via knowledge workers' satisfaction (Shahzadi et al., 2021). This scenario motivates global IT ¯rms to invest considerable money in di®erent online learning platforms, conducting virtual training sessions, and human resources (learning champions, coordinators, managers, etc.). A lack of digital skills results in a skill gap and can jeopardise the ¯rm's ability to gain a competitive edge in the changing digital industry (Gartner, 2020). Meeting the cognitive category's necessary skill
demand requires strengthening the learnability of the existing workforce through e®ective knowledge management practices (Ra et al., 2019).
However, though many initiatives are taken across the global IT organisation towards e®ective knowledge management, most of them lack e®ectiveness, resulting in a shortage of digitally skilled workforce (Sivaraman, 2020). There exists an in- terrelation between strategic foresight of organisation leadership and e®ective knowledge management (da Silva Nascimento et al., 2021). When leaders think about digital skill-building, they should primarily focus on identifying and investing in a capable workforce to make digital technology e®ective for the organisation. Contrary to popular belief, digital skill transformation is more about people than technology, and leadership teams often overlook people (Frankiewicz and Chamorro- Premuzic, 2020). Further scope exists in carrying out data-driven analysis to un- derstand the fundamental problem across the organisation and carry out statistical modeling to identify attributes that are primarily in°uencing digital learning. Establishing such a model can help organisations decide with better precision re- garding di®erent measures to improve the in-house reskilling e®ectiveness.
The purpose of this research is to carry out a holistic analysis and get a 360o view of the current digital skill transformation problem involving di®erent stakeholders — Delivery Partners (DP), Delivery Managers (DM), relevant technology Subject Matter Experts (SMEs), Human Resource (HR) key personnel, Talent Development Team (TDT) key personnel, Talent Acquisition Team (TAT) key personnel, Re- source Management Team (RMT) key personnel and existing employees across the business unit. This analysis helps identify key performance indicators (KPIs) that in°uence existing workforce learning and reskilling. This research also uses statistical modeling to understand the in°uence of di®erent identi¯ed KPIs on existing employees' digital skill-building and how underlying organisation-level activities and processes impact the initiative.
The complex nature of the digital skill transformation process involves signi¯cant commitments from both the organisational level and individual employees. This paper focuses on the following research questions:
RQ1. What are the critical performance measures that a®ect the e®ectiveness of an
IT service ¯rm's digital skill transformation initiative?
RQ2. How do individual and organisational level measures impact IT service ¯rms'
digital skill transformation journeys?
2. Review of Literature
Technology has become the mainstream of innovation recently (Kumar et al., 2021). Knowledge-driven societies like IT service ¯rms' acquisition, sharing, nurturing, and usage of knowledge become a vision for management (Tallapalli, 2018). Software development is knowledge-intensive and requires collaborations across di®erent stakeholders of the ¯rm. In line with the organisational goals and growth
opportunities, every IT ¯rm strategizes its knowledge management practices and deploys them to gain a competitive advantage in the industry (Andriani et al., 2019; Vasanthapriyan et al., 2017).
Knowledge-intensive organisations are characterised by the organisation's pro- active approach toward building knowledge and elevating employees' skills organi- sation-wide. Here, skill or knowledge transformation of individuals or team members is essential (Kirchner and Cudanov, 2011). Overall knowledge management and skill transformation directly impact employees' performance in the workspace (Ahmad et al., 2018) and thus become the need of the hour for the IT ¯rms.
Digital transformation in line with Industry 4.0 is very resource-intensive, com- plex, and more complicated than traditional technology transformation (McKinsey and Company, 2018). In this era, digital technologies like Arti¯cial Intelligence (AI), Machine Learning (ML), big data, and cloud platforms are in high demand, and this leads IT ¯rms to think about e®ective skill transformation of their existing workforce (Ghobakhloo and Iranmanesh, 2021). Understanding the maturity level of knowl- edge transfer e®ectiveness among team members in an IT service organisation in digital technologies is crucial. Organisational understanding, valuing, and adequate support for knowledge acquisition, knowledge conversion, knowledge application, and knowledge transfer are critical in any organisation's successful knowledge transition (Ginting, 2020). Research has shown that skill transition e®ectiveness is low across IT service organisations. Individual readiness, capability, history of suc- cessful knowledge transformation, learning organisational culture, and adequate corporate support to its employees play an essential role in the skill transformation initiatives (Tornjanski et al., 2020; Olteanu, 2018).
Knowledge management is treated as a managerial fad that focuses on knowledge generation, dissemination, and utilisation. It is argued that knowledge and skill management's objectives are not to build knowledge management systems (KMS) but to increase an organisation's value by capitalising on the potential value of knowledge (Jang et al., 2002). Organisational culture and knowledge management in°uence corporate innovation, which is considered a strategic driver for a ¯rm to gain a competitive advantage. Knowledge is the primary resource to gain a com- petitive advantage over rival ¯rms (Zhang and Zhang, 2017). E®ective knowledge management and skill transformation heavily depend on organisational culture (Abdi et al., 2018; Carlile and Rebentisch, 2003).
In the current digital era, gathering information or data is no longer a di®eren- tiating attribute. The onus creates knowledge and codi¯es it into the organisational routine (Datta and Acar, 2010). Forming strategic alliances with partners is essential to sustain within the knowledge industry and gain a competitive advantage. Stra- tegic alliances can be considered strategic knowledge to develop skills and creativity and in°uence organisations' human capital (Widodo, 2015).
The digital economy depends on knowledge. The ultimate objective of a knowl- edge-driven organisation is to apply skill transformation and knowledge building toward organisational performance improvements and gain a competitive advantage
(Tikakul and Thomson, 2018). Organisations' business strategies shifted from managing tangible assets to intangible resources. Organisations need to provide learning and knowledge management infrastructure to explore organisation's knowledge wealth (Lytras and Pouloudi, 2003).
Employees' knowledge management directly in°uences their productivity in day- to-day work (Shujahat et al., 2021). The level of technological innovation in the software industry during the past decade is unparallel in human history, which creates skill gaps across IT organisations. This skill gap leads global IT ¯rms to think about the pillars of technological transformation like people, process, technology, and culture to take strategic planning to prepare employees' digital skills (Sivara- man, 2020). Most of the time, a ¯rm's approach is similar to all employees and does not consider that one employee's learnability may di®er. To e®ectively transform the employees' skills, organisations need to access the employees' learning styles before recommending any training program or skill transformation initiatives. It is found that age group, work experience, job role, workspace hierarchy, geographic location, and workforce diversity can play an essential role in determining the learning style of global IT service companies (Kellogg, 2021; Tikakul and Thomson, 2018; Lele and Nayak, 2017; Krome, 2014).
The Indian IT industry's business model mainly provides low-end human resources-intensive software services to Western multinationals. But this industry is arising as one of the vibrant sectors in the Indian economy. To gain competitive advantages and cope with dynamic technology advancement, IT ¯rms are trying to implement innovative culture and adopt niche digital technology skills. The pre- vailing trend in the digital skill areas is likely to generate new exciting opportunities in the recent future (Cherian and Kamalanabhan, 2019; Baragde and Baporikar, 2017).
Digital technology transformation changes the employee's skills that an organi- sation needs to succeed (Ostmeier and Strobel, 2022). The industry-wide focus on digital technology skill areas immediately demands human resource development and intern reskilling of the existing workforce into digital technology areas to improve ¯rms' market performance and reduce the talent gap (Rishabharaja and Nisha, 2021; Uraon and Gupta, 2020). Global IT service companies respond by training employees in relevant areas. Still, they disregard the question of adequate training and prepare managers capable enough to lead the initiatives in the current data-driven era (Carillo, 2017).
The reviewed literature discussed the importance of knowledge transformation and skill set building, focusing on the digital technologies in the IT service industry. The existing literature lacks exploring and quantifying the impact of di®erent organisational level attributes on such skill transformation initiatives. As against existing literature, this paper is uniquely positioned in two ways. First, this paper investigates the global IT service ¯rms' challenges while carrying out their skill transformation journey in digital technologies. Second, this paper analyses and builds a statistical model to show how di®erent attributes impact the e®ectiveness of
¯rms' skill transformation initiatives. Subsequently, a discussion with managerial implications is put forward.
Based on the literature review and research questions (RQ1 and RQ2), the fol- lowing alternate hypothesis is framed:
H1 (Project Environment): Organisations' project environment positively
in°uences employee's learning e®ectiveness.
H1 (Training E®ectiveness): Organisations' training e®ectiveness positively
in°uences employee's learning e®ectiveness.
H1 (Reading Time): Individual employees' reading time positively in°uences
employee's learning e®ectiveness.
H1 (IT Experience): IT experience of individual employees positively in°uence
employee's learning e®ectiveness.
3. Objectives
This paper's objectives align with the rationale of the research and the research gap presented in the literature review section. The ¯rst objective is to quantify the ine®ectiveness of reskilling measures across a global IT ¯rm in terms of revenue loss and use it as an indicative measure across similar business units. Further, the aim is to get a 360o view of the problem by considering inputs from di®erent stake- holders — DP, DM, SMEs, HR, TDT, TAT, RMT, and existing employees from the largest business unit of the global IT ¯rm. The key objective is to identify di®erent KPIs most in°uential to employee reskilling initiatives and develop a statistical model to understand their in°uence. Establishing such a model will help us know whether the said KPIs signi¯cantly impact skill transformation initiatives and grasp the distinctive information worthy for IT forms to consider in their knowledge management and skill transformation initiative.
4. Methodology
4.1. The source of data and sample frame selection
This study's research design mainly considers primary qualitative data obtained through Focused Group Discussion (FGD), in-depth personal interviews, a primary survey among DP/DM of one sub-business unit, and a second primary survey across all the employees of the largest business unit of a global IT ¯rm.
In terms of books and internet-based resources, secondary data sources are con- sidered while carrying out the analysis. The KPIs identi¯ed using these data help comprehend their impact on the existing employees' skill transformation and read- iness toward digital skill-based projects.
4.2. Quanti¯cation of the problem
Di®erent business units face challenges in e®ectively reskilling the existing workforce and deploying them in challenging projects where rigorous client interview(s) and
digital skill sets are in demand. One primary survey conducted among delivery partners (questionnaire sent through e-mail) of one sub-business unit reveals that the current reskilling problem results in a potential loss of $1,223 K to the corre- sponding sub-business unit during Q2 of FY: 2020–2021. The analysis also shows that, on an average, only 13% of the ¯rms' internal workforces are deployable in a competitive environment (see Table 1).
4.3. SME feedback and suggestions — Focused group
discussions (FGD)
After quantifying the problem, FGD was conducted involving very knowledgeable
SMEs chosen from pan-Indian locations. Nine SMEs participated in the discussion, and one trained moderator moderated the process. The FGD revealed several potential issues and discussed how to e®ectively handle the skill transformation problems. A summary of the key points and suggestions are shown as follows (see Table 2).
4.4. Other key stakeholders' feedback and suggestions — In-depth
personal interview
As part of the root cause identi¯cation exercise of the skill transformation problem,
key personnel from TDT, HR, RMT, and TAT are requested for personal interview sessions. These in-depth interviews are conducted over organisation provided Microsoft Teams and/or phone. A summary of the key insights and suggestions from the interview sessions are listed in Table 3.
4.5. In-house employees' feedback from the largest business
unit — Primary survey
One primary survey was conducted among the existing employees of the largest
business unit across multiple geographic locations (India, USA, Mexico, UK, and mainland Europe) through an online questionnaire to complete the 360o analysis. The organisation's in-house survey platform helps in administrating the primary survey. This survey was responded to by 1072 employees across di®erent projects and locations of the business unit. Thirteen mandatory questions (3 of which have one interactive question based on the response) were presented to the associates to gather information. One free °ow text box (as an optional 14th question) was pre- sented, and respondents were encouraged to comment on what they feel in the current context critically. The survey was kept strictly con¯dential, and no identi- ¯able information like Name, employee number, project name, gender, grade and location were stored as part of the survey. The author performed the data screening to check for any missing values and con¯rmed that all the responses were complete to start a further analysis.
Likert's ¯ve-point scale was used for ordinal or categorical data capture while forming questionnaires for the survey.
Table 2. SME FGD key highlights.
Serial no. Key focus SME suggestions
1 Technical SMEs are burdened with
managerial and operational work.
2 There are the role and job-content
mismatches for senior technical candidates.
3 Junior employees' skill level is usually lower than expected, whereas client expectations
are high. A signi¯cant number of recruits are below the average category.
4 The project leadership team has very minimal
or no technical understanding and skills.
5 Internal online learning platforms and
training are not e®ective.
Source: Author's compilation based on FDG.
Table 3. Key stakeholders insights and suggestions.
Technically skilled employees should not
be burdened with operational work.
Technology growth path should be celebrated more and needs to be given
prime importance organisation-wide.
The recruitment policy needs to be re-
looked. The prime focus should be given to the premier educational institutes while recruiting candidates.
Supervisors/managers need to play a
signi¯cant role in ¯rst upbringing themselves and their team. The senior leadership team needs to re-look at the traditional approach of giving operational managers a leadership role.
Currently, the technology life span is drastically reduced. This situation makes some skillsets obsolete fast. E®ective reskilling plans and project-
level long-term investments are needed.
Serial No. Stakeholders Insights Suggestions
1 TDT Personnel 1. Only self-learning via online
mode cannot provide a ho- listic picture and make a candidate's digital project ready.
2. Identi¯ed candidates lack the passion for learning new digital skills.
2 HR Personnel Key business unit stakeholders
do not consider learning a rigorous a®air.
3 RMT Personnel Business units and projects are
not seriously interested in investing time and money towards the upbringing of existing employees.
Table 3. (Continued)
Serial No. Stakeholders Insights Suggestions
4 TAT Personnel In-house technical SMEs are
often unavailable during recruitment sessions because of their deep involvement in the project and client delivery.
1. Business units should plan for SEM time
to screen quality candidates during re- cruitment drives.
2. Emphasis should be given to selecting
above-average candidates while recruit- ing (both Trainees and experienced professionals).
Source: Author's compilation based on personal interview sessions.
4.6. Statistical model development
The author has considered a three-stage approach to study how di®erent KPIs in°uence associates' skill transformation in digital technologies and their readiness to take challenging assignments. In the ¯rst stage, an analysis of di®erent attributes gathered through the primary survey is performed. In the second stage, KPIs are analysed and chosen. Lastly, a statistical model is developed using Ordinal Logistic Regression to understand and quantify how selected KPIs in°uence associates' skill transformations and readiness to take challenging technical engagements.
4.7. Statistical and analytical software/tolls used
Microsoft Excel and Data Analytics software R is used for descriptive statistics and statistical model development.
5. Analysis and Results
5.1. Descriptive statistics and analysis
5.1.1. Distribution of respondents — Total IT experience and current grade
Based on the primary survey result, the distributions of respondents classi¯ed based on their total IT experience and current grade are shown in Tables 4 and 5.
Table 4. Distribution of respondents — Total IT experience.
IT experience No. of responses
0 to 3 years 78
3þ to 6 years 128
6þ to 10 years 202
10þ to 15 years 417
> 15 years 247
Source: Author's derivation based on the Primary Survey Data.
Table 5. Distribution of respondents — Current grade.
Current grade No. of responses
Up to SE or Equivalent 144
ITA & AST or Equivalent 495
ASOC or Equivalent 319
CON or Equivalent 90
Above CON or Equivalent 24
Source: Author's derivation based on the Pri- mary Survey Data.
Notes: SE — System Engineer; ITA — Infor- mation Technology Analysist; AST — Assis- tant Consultant; ASOC — Associate Consultant; CON — Consultant.
The response pattern shows that the primary survey received responses from employees across all the experienced bands and grades.
5.1.2. Distribution of respondents — Reading time/week
From the above analysis (see Table 6), only a few number of current employees have regular reading habits. This reading time includes any technical/non-technical with all possible channels (hard copy, soft copy, online learning platforms, etc.). The result shows that only 7.7% of respondents (82 out of 1072) study more than 2 h per day, which is negligible.
Further analysis shows that the workforce who regularly read nine or more hours per week (Total: 231) comprises employees with 10þ years of experience (71.43%). The existing workforce in the lower experience range of 0 to 3 years (Juniors) and 3þ to 6 years (sub-juniors) are the lowest at 5.2% and 8.2%, respectively, which is alarming.
Junior/sub-junior associates with low reading likelihood may signi¯cantly hinder reskilling initiatives. Firms' may relook their recruitment policy, and emphasis may
Table 6. Distribution of respondents — Reading time/week.
Reading time No. of responses
0 to 2h 240
3 to 5h 354
6 to 8h 247
9 to 14h 149
> 14h 82
Source: Author's derivation based on the Primary Survey Data.
Preparedness Total number Percentage
Fully prepared 164 15%
Prepared to a large extent 229 21% Have some preparation 403 38%
Insigni¯cant preparation 217 20% No preparation 59 6%
Source: Author's derivation based on the Primary Survey Data.
be given during recruitment to those academic institutions/Universities renowned for their academic excellence and rigor across the country.
5.1.3. Respondents feeling about their current state — Employee readiness
for digital projects
The analysis of individual readiness (self-assessments) to take digital skill assign-
ments is carried out. These details are shown in Table 7.
The primary survey data shows that 36% of the existing workforces feel either
fully prepared (15%) or ready to a large extent (21%) to take challenging digital technology assignments. Most of the workforces feel they lack relevant digital skill sets that have market demand. The analysis also clearly shows that among the 393 respondents (36% of the sample) who believe they have acquired adequate digital technical skills, mostly (□ 63%) comprise the senior workforce with 10þ years of experience. Table 8 depicts this in detail.
It may be alarming to note that more than 80% of the relatively junior workforce pool (up to 6 years of experience) considers themselves lacking in knowledge and skills to take up challenging assignments. These results may lead to any of the three possible conclusions — recruited junior and sub-junior workforce are not competent enough, are not getting enough opportunities, or are not motivated to build/develop technical competency. The analysis is conducted among the responses of self- declared prepared (including prepared to signi¯cant extent cases) respondents (a total of 393 samples) to understand what factors help them to build their digital competency (see Table 8). Most skilled respondents consider \on the job" working
Table 8. Distribution of skilled workforce — IT experience wise.
Years of experience Number of skilled workforce Percentage
0 to 3 years 22 5%
3þ to 6 years 50 13%
6þ to 10 years 75 19%
10þ to 15 years 153 39%
> 15 years 93 24%
Source: Author's derivation based on the Primary Survey Data.
Table 9. E®ective digital skill transformation mediums.
Digital skill transformation mediums No. of employees preference
On-job working experience 221
Instructor lead trainings 29
Attending post-graduate program 47
In-house online learning 73
Expert mentoring 23
Source: Author's derivation based on the Primary Survey Data.
knowledge mostly helpful in their skill transformation journey. In-house online learning and joining postgraduate programs with academic institutes are other ef- fective measures (see Table 9).
In-house instructor lead technical training seems to be mostly ine®ective in the knowledge transformation journey, and only 7.4% of the respondents think there are bene¯ts from such training programs. The current time can be an excellent time for the organisation to introspect the e®ectiveness of the current instructor-led training programs and see how the training can bene¯t the workforce.
5.1.4. E®ectiveness of in-house online learning platforms
The organisation continues investing a signi¯cant amount of money in online learning platforms like Udemy, LinkedIn learning, Safari books, and its in-house learning platform. The organisation needs to know how e®ective all these platforms are for the existing workforce's digital skill transformation initiative. Feedback from SMEs via FGD con¯rms that organisations' in-house learning platform is ine®ective, but Udemy and Safari books are better. The primary survey results show that around 74% of the workforce thinks organisations' online learning modes have average or below average e®ectiveness (see Table 10). Further analysis is conducted among the respondents who rated the usefulness of online learning platforms on a larger scale. The outcome shows that only 6% of junior associates (0 to 3 years Exp) and 10% of sub-junior associates (3þ to 10 years Exp) consider the online learning platforms e®ectively helping them in skill transformation initiatives (see Table 11).
Table 10. E®ectiveness of in-house online learning platforms.
E®ectiveness of online learning platforms Employee's responses
Not at all e®ective 70
Somewhat e®ective 285
Average e®ective 437
Highly e®ective 259
Extremely e®ective 21
Source: Author's derivation based on the Primary Survey Data.
Table 11. Associate experience and e®ectiveness of in-house online learning platforms.
Experience range Total response Percentage of response
0 to 3 years 17 6%
3þ to 6 years 28 10%
6þ to 10 years 50 18%
10þ to 15 years 120 43%
> 15 years 65 23%
Source: Author's derivation based on the Primary Survey Data.
The thought that online learning platforms would eventually transform junior/ sub-junior associate skill levels and make the existing workforce market-ready with digital skills is super¯cial. It is time for the organisation to re-think its knowledge management and skill transformation strategy.
5.1.5. E®ectiveness of learning champions in skill transformation journey
The organisation selects employees from individual projects and deploys them across business units to facilitate learning activities. These associates are referred to as learning champions of individual projects. It is evident from the analysis that these learning champions (LCs) are playing a very ine®ective role in employees' digital skill transformation (see Table 12). The learning champions of di®erent projects (including their supervisors) somehow gather some data points and circulate a report to senior management. These may be the probable cause of the ine®ective role played by learning champions. Putting unwilling candidates forcefully into the LC position by purely \excel" driven supervisors may also be counterproductive.
Based on the analysis and FGD inputs, the author suggested that senior lead- ership of the organisation consider reports as secondary items and strategize how to facilitate actual learning and skill transformation.
5.1.6. Current supervisor/managers technical competency and acumen
Employees' current supervisor/manager behavior (Agarwal et al., 2022), technical competency, and understanding play a signi¯cant role in the employees' learning
Table 12. E®ectiveness of LCs.
E®ectiveness categories Responses Percentage of responses
Very high value 48 4%
Somewhat value 207 19%
Not sure 446 42%
Very less value 128 12%
No value 243 23%
Source: Author's derivation based on the Primary Survey Data.
B. Talukder
350
300
250
200
150
100
50
0
Supervisor/Manager TechnicalCompetency/Acumen
346
297
180 180
69
Exteamly Knowledgable
Knowledgable Less
Knowledgable
Not Knowledgable
Purely Operational Person
Source: Author's derivation based on the Primary Survey Data.
Fig. 1. Current supervisor/manager's technical competency/acumen.
journey. Analysis reveals that more than 60% of the respondents think their su- pervisor/manager does not possess enough technical skills (see Fig. 1). The super- visor/manager category which does not have any technical skills and is only interested in operational work can negatively impact the project environment.
5.1.7. Current project environment — Mentoring and encouragements
in digital skill transformation
The project's mentoring and encouragement are critical in existing employees' res-
killing journey and a quest for a digital skillset. The primary survey response and analysis clearly show that only 16.6% of respondents think they receive e®ective mentoring from their project. A total of 68.5% of respondents believe there is either ine®ective mentoring or no mentoring in their current project (see Fig. 2).
A similar line analysis of respondents' current project environment (see Table 13) suggests that most of the workforce (60%) lack encouragement in learning from their project. The analysis also reveals that this is a probable cause of ine®ective leader- ship; learning is seen as only data collection activities coupled with improper or no
In-Project Mentoring
496
500
400
300
200
100
0
41
238
136 161
Effective & Adequate
Mentoring
Effective but not adequate
Moderately Effective
Mentoring
Ineffective Mentoring
No Mentoring
Source: Author's derivation based on the Primary Survey Data.
Fig. 2. In-project mentoring of associates.
Table 13. Project environment.
Current project environment Responses Percentage of response
Learning is in the DNA of the project 60 5.6
Excellent encouragement in learning 372 34.7
Ine®ective encouragements 202 18.9
Learning data collected only for generating metrics 319 29.8 Non-technical leadership, no proper planning, no encouragement 119 11.1
Source: Author's derivation based on the Primary Survey Data.
planning by the project leadership. These results can be alarming and can negatively in°uence associates' digital skill transformation, job satisfaction, and day-to-day client technical delivery. The current observations inevitably raise the question of the managerial/leadership capability of some managers in the studied business unit across multiple geographic locations.
Further analysis suggests that only a handful percentage of respondents in the junior (0 to 3 years) and sub-junior (3þ to 6 years) category (6.6% and 9.4%, respectively) think that their current project environment encourages them to learn. The current situation may conclude that most projects failed to promote their junior workforce. Introspection is needed to ¯nd out the probable cause and address this aspect. Based on the experience, the author may point out a few possibilities as potential causes for this issue.
The leadership team's disconnection from team members, seniors' bossy attitude, an ego problem, high power distance in the project, technically incompetent su- pervisor/manager, and most importantly, high operational hazards for project ex- ecution contribute the most.
There is a high probability that supervisors/managers lacking in technical un- derstanding may experience challenges in encouraging associates in their learning journey and doing/arranging proper mentoring. The correlation coe±cients between three ordinal datasets, namely \Supervisors Technical Acumen", \Mentoring" and \Current Project Mentoring" are calculated using Spearman Rank Correlation (Croux and Dehon, 2010) and given in Table 14. The result indicates that the supervisor/manager's technical acumen has a signi¯cant positive correlation (Hair et al., 2019) with the project environment. The project environment has a signi¯cant positive correlation with project mentoring.
Table 14. Correlation matrix using Spearman's rank correlation.
Supervisor's technical acumen Mentoring Project environment
Supervisor's technical acumen 0.405 0.509
Mentoring 0.405 0.484
Project environment 0.509 0.484
Source: Author's own derivations.
We can statistically infer that the higher the supervisor/manager's technical competency, the better the project can provide associates with learning encourage- ment and mentoring and help them in their reskilling journey.
5.1.8. Existing workforces' skill transformation journey — Challenges/Hurdles
One of the most important contexts in the digital skill-building journey is the challenges faced by the organisations' existing workforce. It is the responsibility of all relevant stakeholders to understand the workforce's problems and address them accordingly to facilitate digital skill-building. The analysis and the result are shown in Fig. 3.
The result clearly shows that only 16.6% of the respondents (178 total) do not face any challenge. But at the same time, more than 80% of the respondents face di®erent challenges that they consider create hindrances in their digital skill trans- formation journey. Too much client billable work pressure is a signi¯cant problem for the associates, followed by not getting a fair opportunity and too much non- technical workload. This outcome aligns with SME feedback gathered during FGD mentioned in Sec. 3.3.
The relevant stakeholders' responsibility, including the business unit's senior leadership, is to ensure that the existing workforce gets suitable skill transformation opportunities and is less burdened with multiple operational works.
5.1.9. E®ectiveness of the in-house trainings
Most of the respondents (□ 50%) consider that the in-house training provided is not fully e®ective, and this training is not helping them much in their digital skill transformation. Simultaneously, about 36% of the respondents consider in-house training helpful. About 14.5% of the associates say they are yet to get an opportunity to attend any training in digital skill areas. The analysis is shown in Fig. 4.
Further analysis was performed on the respondent's suggestion to improve in- house training. The study is given in Table 15. About 39% of respondents consider labs/hands-on sessions inadequate, and 46% think a dedicated sandbox environment
Challenges Faced by Existing Workforce
372
400
300
200
100
0
178
228 285
9
No Challenges Too much billable work
pressure
Burdened with too much non technical work
Working in legacy systems and not gettng opportunities
Not interested in learning
niche technical skills
Source: Author's derivation based on the Primary Survey Data.
Fig. 3. Challenges faced by existing workforce.
Source: Author's derivation based on the Primary Survey Data.
Fig. 4. In-house training e®ectiveness.
Table 15. Respondents' suggestions — Training e®ectiveness improvements.
Training improvement suggestions Responses Percentage of response
No improvement needed 64 7%
Provide quality training material 73 8%
More labs/hands-on 355 39%
Dedicated sandbox for practice 427 46%
Source: Author's derivation based on the Primary Survey Data.
is required for practice. The learning department should prioritise hands-on lab sessions and the availability of sandbox environments while planning any in-house training. Once addressed, we may expect more e®ective skill-building among the existing employees.
5.1.10. Existing workforce redeployment & challenges faced in last 2 years
Existing employees who get a release from a project and deploy in a new project may face several challenges. An analysis of respondents who changed their project one or more times during the last two years (see Table 16) and the outcome show that around 40% of the respondents changed their project within the past two years. It is
Table 16. Employees' project change during last 2 years.
Redeployment in past 2 years Response Percentage of response
No project change 644 60%
1 time change 280 26%
2 Times change 100 9%
More than 2 times Change 48 5%
Source: Author's derivation based on the Primary Survey Data.
200
150
100
50
0
Experience Band Wise Release in Past 2 Years
162
120
71
47
28
0 to 3 Yrs 3+ to 6 Yrs 6+ to 10 Yrs 10+ to 15 Yrs > 15 Yrs
Source: Author's derivation based on the Primary Survey Data.
Fig. 5. Experience band-wise release.
also interesting to see that more releases happen for the associates in the 10þ to 15 years' experience band (38%), followed by > 15 Years' experience band (28%) and 6þ to 10 Years' Experience band (16.6%) (see Fig. 5). The earlier analysis reveals that respondents who are proactive in their digital learning initiative and made themselves skilled and ready for the challenging assignments to a more considerable extent belong to these senior categories only.
Business units should critically investigate this aspect beyond thinking workforce cost reduction measures only while releasing senior workforce who are technically skilled. It is also evident from earlier analysis that the junior and sub-junior pool of associates may lack skills, and they are sometimes detached from learning and upskilling themselves. In the current context, senior associates may play a critical role in mentoring and technically contributing to the project e®ectively. Keeping a signi¯cant focus on cost reduction and not preserving senior technical candidates can be detrimental to any technical knowledge-building initiative. It will negatively af- fect client delivery in the future.
Further analysis of the respondents' data that got released during the last two years reveals the following signi¯cant problems faced by them during the rede- ployment process (see Table 17):
5.1.11. Digital skill transformation facilitation — Organisational support
The existing workforce looks for organisational support and encouragement during their digital skill transformation journey. In the primary survey, respondents were asked to select up to three organisation-level support they think might help them acquire digital skills. Analysis of the response and top four suggestions from respondents are shown in Table 18.
Respondents are primarily looking for strengthening alliance partnership and dedicated classroom training, part-time study in reputed universities/institutions with Organisational sponsorship and full-time short duration (8 to 10 weeks) study in premier institutes. The current project or business unit has a signi¯cant role in
Table 17. Redeployment challenges after release from existing project.
Serial No. Category Challenges faced
. Senior employees are forced to take project management
or operational roles.
. Projects do not have any structured onboarding plan
based on technology pattern mapping.
. A biased supervisor or manager sometimes has ethical
issues.
. Unhealthy working atmosphere — technology work is
not earning signi¯cant respect.
. Projects are not motivating an enthusiastic and skilled
workforce in digital skill-building.
. Lack of proper mentoring
3 Appraisal . Faced appraisal cycle issue (project release results in a
lower performance band)
4 Supervisor/Manager . Less competent supervisor/manager.
. Severe lack of transparency from the supervisor.
. A supervisor is not open to considering new ideas or
points of view.
. The existing workforce's °uidity is not planned.
Source: Author's own derivations from primary survey responses.
providing end-to-end plans, from practical training to employees' deployment to the right project. Total/partial reimbursements of postgraduate degree/diploma (of selected institutes/universities) carried out by associates in their interest may en- courage others to learn.
Table 18. Suggested organisational supports.
Organisational support Responses
Reimburse fully/partially postgraduate degree/diploma from Premier Universities/
Institutes.
Set up collaboration with leading Universities/institutes and facilitate company-
sponsored study (Part–time).
333
440
Invest in associates and send them to premier institutes full-time for a short duration. 422 Strengthen alliance partnership and e®ectively conduct in-class training and allow
associates to attend that training dedicated way.
E®ectively leverage highly skilled associates in mentoring others. 334
Provision \Shadow Resource" concept in the project 324
The project must provide an end-to-end plan starting from e®ective learning to
deployment.
The project/Business unit failed to utilise my niche skill sets. 276
Source: Author's derivation based on the Primary Survey Data.
5.2. Critical performance indicators and their impact on digital skill
transformation
The analysis carried out so far suggested that signi¯cant factors in°uencing the skill
transformation are employees' total IT experience, time spent on reading, current supervisor/manager technical skillset/acumen, training e®ectiveness, good mentor- ing, and project environment. The author considers the respondent's self-judgment of readiness to take on digital technology assignments to measure e®ective digital skill transformation. Table 19 shows the dependent variable, independent or pre- dictor variables, and their possible role in the analysis.
The above KPI identi¯cation and analysis of their possible impact leads us to build a conceptual model shown in Fig. 6.
The main descriptive statistics of the considered KPIs is shown in Table 20. One crucial aspect considered in the KPI selection process is avoiding multi-collinearity among the explanatory variables.
Table 19. Digital skill transformation e®ectiveness and variables.
Variables/KPIs Property Category Remarks
Total IT experience (EXP) (in Years)
Reading time (RT)
(in h/week)
E®ective mentoring
(EM)
Current supervisor/ managers technical
competency (CSTC)
Project environment
(PE)
Training e®ectiveness
(TE)
Associates' readiness for
challenging work (AR)
Higher is better Predictor variable Considered as KPI in further analysis.
EXP has +ve in°uence on the dependent variable. This KPI is individual employee-dependent.
Higher is better Predictor variable Considered as KPI in further analysis.
RT has +ve in°uence on the dependent variable. This KPI is individual employee-dependent.
Higher is better Predictor variable Considered as KPI in further analysis.
EM has +ve in°uence on the dependent variable. This KPI is organisation-dependent.
Higher is better Predictor variable This has strong correlation with EM.
CSTC is not considered for statistical model development to avoid possible \multicollinearity" issue. This KPI is organisation- dependent.
Higher is better Predictor variable Not considered for statistical model
development. The argument is same as above. This KPI is organisation-dependent.
Higher is better Predictor variable Considered as KPI in further analysis.
TE has +ve in°uence on the dependent variable. This KPI is organisation-dependent.
Higher is better Dependent variable Considered as KPI in further analysis.
Source: Author's own derivation.
Individual-Specific Measures
-EXP (+ve impact)
-RT (+ve impact)
Digital Skill Transformation
Organisation
Specific Measures
-EM (+ve impact)
-TE (+ve impact)
Source: Author's own derivation.
Effectiveness Measure
-AR
Fig. 6. E®ect of individual and organisation speci¯c KPIs on skill transformation e®ectiveness.
Table 20. Descriptive statistics of selected KPIs.
KPIs Frequency distribution Mode
EXP 0 to 3 years: 7.3%
3þ to 12 years: 12%
6þ to 10 years: 18.9% 10þ to 15 years: 38.9% > 15 years: 23.1%
RT 0 to 2 h: 22.4%
3 to 5 h: 33%
6 to 8 h: 23.1%
9 to 14 h: 13.9% > 14 h: 7.7%
EM Adequate and e®ective: 3.9% E®ective but not adequate: 12.7%
Moderate e®ective: 15.1%
Very less and ine®ective: 22.2%
No mentoring: 46.3%
TE Not helpful: 15.8%
Somewhat helpful: 34.1%
Helpful: 25.5%
Very much helpful: 10.4%
Not attended any training: 14.4%
AR Prepared: 15.3%
Prepared in large extent: 21.4% Some preparation: 37.3%
No Signi¯cant Preparation: 20.3% No Preparation: 5.5%
Source: Author's own derivation.
10þ to 15 years
3 to 5 h
No mentoring
Somewhat helpful
Some preparation
3. Statistical model development
This study aims to recognise critical KPIs' in°uence on respondents' readiness for digital technology work through a statistical model. Here the dependent variable (AR) is ordinal. Accordingly, the Ordinal Logistic Regression model (STATA, 2020) with KPIs — EXP, RT, EM and TE is identi¯ed in Sec. 4.2 as the predictor variable and AR as the dependent variable. The results are shown in Table 21.
The model clearly shows that EXP, RT, EM, and TE positively impact respon- dents' digital skill transformation and readiness for challenging projects. Apart from the EXP, all three predictor variables are signi¯cant at a 95% con¯dence level, as shown in Table 21. These results suggested acceptance of the alternate hypothesis H1 (Project Environment), H1 (Training E®ectiveness), and H1 (Reading Time) at a 95% level of signi¯cance. EXP may not be statistically signi¯cant in the current dataset. It might be the case that EXP has an insigni¯cant impact on AR at a 95% con¯dence level but is substantial at a 90% con¯dence level. Thus, the alternate hypothesis H1 (IT Experience) can be accepted at a 90% level of signi¯cance.
6. Conclusion and Managerial Implications
It is evident from this study that in the existing workforce's digital skill transfor- mation and readiness towards niche technical skill assignments, factors like reading time, e®ective mentoring, and training e®ectiveness contribute signi¯cantly. It should be the endeavor of all relevant stakeholders to ensure the e±cacy of all these factors.
All the existing workforce of the IT service ¯rm should be encouraged to read more (o®line/online) and focus on their chosen technology. The focus should be on promoting the workforce to read and learn more rather than collecting a few metrics from online learning platforms' access points.
E®ective mentoring is a signi¯cant aspect that directly correlates with current supervisors' technical competency and interning with the current project environ- ment. Senior leadership may think of putting non-technical managers on the oper- ational team and deploying knowledgeable candidates willing to contribute technically in critical decision-making roles. IT is a knowledge industry or becoming so, and there are dying needs for \Playing Captain" to handle the project decisions. Emphasis should be given to ensure the project leadership team is not burdened with operational hazards and does not end up only doing data collection and preparing many reports.
Lastly, most of the existing workforces do not appreciate current training e®ec- tiveness. In the digital skill transformation journey, this is one of the critical parts. Initiatives like enhancing collaboration with global vendors, setting up a partnership with premier universities/institutes, encouraging part-time and short full-time study, and providing suitable training environments can signi¯cantly improve the current situation. Organisations can create an e®ective training environment
through quality trainers and mentors, quality study material, ample sandbox environments for hands-on activities, and appropriate SME involvement by bal- ancing SME client delivery and organisation-building activities. Appropriate SME involvement substantially impacts mentoring and the e®ective intake of the new workforce. The individual projects need to make end-to-end plans for their employees' training and deployment, without which other initiatives may lose their e®ectiveness.
7. Limitations and Way Forward
This research investigates a 360o view considering all relevant stakeholders' inputs (located across multiple geographies) but concentrates mainly on one of the largest business units of a global IT service ¯rm. This study could have been enhanced by considering similar data across the organisation. Other researchers may consider actual data of the existing workforce deployed in digital projects after clearing one or multiple rounds of client evaluations, if available. These may reveal some more interesting insights about the problem. Others may consider qualitative factors like employees' willingness to be in the comfort zone, technology fear, demand prediction appropriateness and hostile customer environments for future study and enhance- ments. The study reveals that ine®ective digital skill transformation and improper workforce deployment may lead to employees' dissatisfaction. The IT service in- dustry is an industry of high attrition. Other researchers are encouraged to deep- drive and consider the attrition angle and its relation to skill transformation and employees' dissatisfaction levels. This attrition angle can be valid and worth further research in the current era of the \great resignation" period in the IT service industry.
As an early measure, every project requiring digital technology-skilled candidates should be encouraged to develop e®ective planning from training to actual deploy- ment. The project should seek appropriate in-house SME feedback where necessary. Besides, relevant stakeholders should think of the suggestions provided in this re- search and start piloting some of them on a smaller scale to see their e®ectiveness. Once successful, the organisation may scale up these small initiatives to ful¯ll more signi¯cant needs.
Acknowledgments
The author is grateful to the journal's anonymous referees for their helpful sugges- tions to improve the quality of the article. Usual disclaimers apply.
Thanks to Mr. Lakshman Akella, Delivery Head, for bringing the digital skill transformation challenge to my notice and reviewing and providing insights on the primary survey questionnaire. The author is thankful to Mr. Sumit Ghosh, Solution Architect, for providing comments that improved the paper.
Appendix A. Primary Survey Questionnaire
Survey Title: Digital Skill Transformation and Knowledge Management Challenge in the Organisation
Welcome to the survey. Di®erent business units are currently facing challenges while deployingexistingemployeesfordigitalskillspositions(likeAI/ML,DataScience,Cloud, to name a few) in competitive environments. The purpose of this survey is to understand the problem from the employee's point of view and suggest corrective measures based on the responses we will receive from you. Your answer will help us take appropriate actions in the existing reskilling initiative business unitwise to make the same more useful.
As part of this survey, personally identi¯able information like Name, Employee Number, Gender, Project, Work location, and Business unit will not be captured or stored. This survey response will be considered as con¯dential and will be used only to improve organisation's digital skill transformations initiative for existing employees.
Thank you very much for your inputs and suggestions.
Section-A
1. What is your total IT experience?
o 0 to 3 years
o 3 to 6 years
o 6 to 10 years
o 10 to 15 years
o More than 15 years
2. What is your current designation?
o Up to SE or equivalent
o ITA & AST or equivalent
o ASOC or equivalent
o CON or equivalent
o Above CON or equivalent
2250090-27
B. Talukder
3. During a week how many hours do you generally spent in reading (includes any
type of reading)?
o 0 to 2 h
o 3 to 5 h
o 6 to 8 h
o 9 to 14 h
o More than 14 h
Section-B
1. Do you consider yourself market ready to take challenging/niche skill positions
(e.g. AI/ML, Data Science, Cloud, etc.) across the business units?
o I am prepared to take the position.
o I am prepared to a large extent but need some guidance.
o I have some preparation and can ¯ll the gap through self-learning online
platforms and guidance.
o I have no signi¯cant preparation. I would like to build the skills through
training and expert mentoring.
o I have no preparation so far. I would like to build the skills through
training and expert mentoring.
[
The following question will come up if associate selects either ¯rst or second option of Question#1
1A. Which of the below option helps you most in your reskilling initiative?
o On-job working experience.
o Instructor lead trainings provided by the business unit/project.
o Attending post-graduate degree/diploma/certi¯cate courses with aca-
demic institutions.
o In-house online learning platforms like Fresco Play, Udemy, LinkedIn
learning.
o Expert mentoring from in-house experts or outside of TCS mentors or both.
]
2. As per your experience how you rate e®ectiveness of available online learning platforms like Fresco Play and LinkedIn learning in transforming associates to acquire niche skills?
o Not at all e®ective. Need to have signi¯cant expert training and men-
toring to ¯ll up the gap.
2250090-28
Digital Skill Transformation and Knowledge Management Challenge in a Global IT Service Firm
o Somewhat e®ective but need expert training and mentoring.
o Average e®ective. Suggestion and mentoring from expert will be needed to
¯ll the gap.
o Highly e®ective. The knowledge gap can be ¯lled using online self-study.
o Extremely e®ective in transforming associates. No further interventions
needed.
3. How e®ectively business unit-wise learning champions are helping you in trans-
forming and gaining niche skill sets?
o Learning champions are adding very high value to my learning journey.
o Learning champions are somewhat adding value to my learning journey. o Not sure if learning champions are adding value to my learning journey. o Learning champions are adding very less value to my learning journey.
o Learning champions are adding no signi¯cant value to my learning
journey.
4. How you rate your current supervisor/manager's technical acumen?
o Extremely knowledgeable and technical. Capable of helping associates in
case of technical challenges in his/her own technical areas.
o Knowledgeable and technically capable. Capable of guiding associates in
case of technical challenges in his/her own technical areas.
o Somewhat technically knowledgeable but usually not available to con-
tribute in technical challenges.
o Seems not in technology touch. Only spoke very high-level stu®s or
terminologies.
o No technical acumen as such. Only interested in operational stu®s.
5. Do you get adequate technical mentoring in niche skill areas (AI/ML, Data
Science, Cloud, etc.) in your own project?
o Always get adequate mentoring from knowledgeable seniors/peers.
o Sometimes get mentoring from knowledgeable seniors.
o Mentoring is moderately e®ective as knowable seniors are not accessible
most of the time.
o Very less and ine®ective mentoring in my own project.
o No mentoring as such in my project.
6. How do you rate your current project environment in terms of encouragement
towards learning niche skills areas (AI/ML, Data Science, Cloud, etc.)?
o Learning is in the DNA of almost all the associates starting from Delivery
Partner to junior associate. Majority of the seniors are role model to the team.
o Learning is encouraged and majority of the associates including project
leaders/managers are actively involved in learning.
2250090-29
B. Talukder
o There are not much e®ective learning initiatives taken in the project.
o Learning data is collected just for managing di®erent metrics. No e®ective
learning outcome and deployment planning is done by the project.
o Project leaders/managers are purely non-technical, and work with excels
only. Proper planning and encouragement towards learning journey are completely missing from the project leadership team.
Section-C
1. What major challenges are you facing in your reskilling journey to gain knowl-
edge in niche technology areas (AI/ML, Data Science, Cloud, etc.)?
o I do not face any challenge and already made myself up to the mark.
o I have too much client billable work to do and do not get much time to
spend in learning new technology.
o I am burdened with di®erent non-technical work which kills my e®ective
time. This is impacting my learning initiative.
o I am working in older technology stack and project is not o®ering e®ective
learning opportunity to me.
o I am not much interested in learning niche skills technology stack.
2. Your opinion on e®ectiveness of training towards your reskilling journey: Do feel the trainings attended by you help you in getting desired project in niche areas (AI/ML, Data Science, Cloud, etc.)?
o Not helpful
o Somewhat helpful
o Helpful
o Very much helpful
o I have not attended any training in niche skill areas
[
The following question will come up if associate selects any option other than the last one for above response.
2A. What is your Opinion to improve the Training? o Trainings are good, no improvement needed o Should provide quality training material
o More lab/hands-on time needed
o Should be provided with Sandbox so that hands-on/PoC can be performed
as and when needed
]
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Digital Skill Transformation and Knowledge Management Challenge in a Global IT Service Firm
3. How many times you are redeployed/changed your project in the past two years?
o Not changed my project/redeployed in the past two years
o 1 time
o 2 times
o More than 2 times
[
The following question will come up if associate selects any option other than the ¯rst one for above question.
3A. Please mention two signi¯cant challenges you faced at the time of redeploy- ment Challenges:
]
4. What do you think projects/business unit should do to e®ectively transform you into a market-ready niche skill professional (Please select multiple options if you wish. Maximum number of selections is 3)?
o Reimburse fully/partially post-graduate degree/diploma from premium
Universities/Institutes carried out on self-interest basis.
o Set up collaboration with leading Universities/institutes and facilitate
company sponsored study part time basis (over weekend or during evening).
o Invest on associates and send them to premier institutes fulltime for short
duration (8 to 10 weeks) to build the desired skill sets.
o Strengthen alliance partnership (e.g. with Microsoft, AWS, IBM, etc.)
and e®ectively conduct in-class trainings and allow associates to attend those training dedicated way.
o E®ectively leverage highly skilled associates in mentoring others.
o Associates with less or no experience should be provisioned to shadow an
experienced person for 2 to 3 weeks to gain better contextual knowledge. o Project must provide end to end plan starting from e®ective learning, doing hands-on, mentoring, shadowing, and ultimately deploying to work.
o I have niche skill sets but those are currently not utilised due to inap- propriate work assigned to me. My skill sets should be properly utilised
within the project and in the ISU level.
.
