Data Governance Inherently comes along with TimeTec HR Analytics

Thursday, February 15, 2024 TimeTec 0 Comments


The fact is 90% organizations don’t have proper Data Governance in place. Data Governance department or unit is to handle requirements from regulatory bodies but at the same time, data governance is also keeping balance between Data Asset and Liabilities. 

Data governance framework creates a single set of rules and processes for collecting, storing, and using data. In details, it consists of the policies, rules, processes, organizational structures, and technologies that are put in place as part of a governance program throughout the organization.

It’s also considering as a set of principles and practices that ensure high quality through the complete lifecycle, it’s more to business rather than technology. To implement Data Governance in an organization, normally involves the following steps:

- Identify roles and responsibilities
- Define your data domains
- Establish data workflows
- Establish data controls
- Identify authoritative data sources
- Establish policies and standards

Without a robust Data Governance or information security measures within an organization, your business is at a higher risk of security incidents, such as data breaches, cyberattacks, or insider threats, which can result in financial losses, reputational damage, and legal repercussions. 

To ensure the data governance that compliance to certain recognizable standards, organizations can incorporate ISO27001 international standard that specifies the requirements for an Information Security Management System (ISMS). Because an ISMS is a framework of policies, procedures, and controls that helps you protect your data from various risks and threats. How can you integrate ISO 27001 into your Data Governance program? 

1. Assess your current data state 
Before adopting ISO 27001, you can understand your current data landscape and identify the gaps and weaknesses in the data security practices by using data governance maturity model to evaluate your data capabilities and performance across different dimensions, such as data quality, data architecture, data governance roles, data policies, and data ethics. Or you can also conduct a risk assessment to identify the potential sources and impacts of data breaches, leaks, or losses. 

2. Define your scope and objectives
The scope defines the boundaries of your ISMS, such as the data types, data sources, data processes, data stakeholders, and data systems that are covered by your ISMS. The objectives are to define the expected outcomes and benefits of your ISMS, such as the level of data protection, compliance, and trust that you want to achieve. 

3. Implement your Information Security Management System (ISMS)
After defining your scope and objectives, you need to implement your ISMS according to the ISO 27001 requirements. This involves developing and documenting your data security policies, procedures, and controls that address the specific risks and challenges that you might encounter. You also need to assign roles and responsibilities for data security to your data governance team and other data stakeholders. Moreover, you need to establish mechanisms for monitoring, measuring, and reporting on your data security performance and compliance.

4. Certify and improve your ISMS
The final step is to certify and improve your ISMS. Certification is an optional but recommended process that involves an external audit by an accredited body that verifies that your ISMS meets the ISO 27001 standards. Certification can help you demonstrate your commitment and credibility to your customers, partners, regulators, and other stakeholders. Improvement is an ongoing process that involves reviewing and updating your ISMS based on the feedback, lessons learned, and best practices that you collect from your data security activities.

Data Governance for HR Analytics 

Nowadays, organizations tend to subscribe applications from SaaS (Software as a Service) providers, the SaaS become the production plant for inputting raw data and generating meaningful data output. It is preferable that the solution provider provides extended DaaS (Data as a Service). It would be a plus point if the solution provider complies with ISO27001 certification to ensure data quality and data governance for the particular solutions, allowing you to focus on business value and organizational outcomes.

Subscribing to SaaS & DaaS and ensuring data governance compliance can mitigate the risk management and data breaches, which inherently core governance components. These compliances will cover the scope related to the applications that you have subscribed to, such as TimeTec HR Suite which related human resources department of an organization. 

For your information, TimeTec has been ISO27001 certified organization since 2018 and enhanced with ISO 27017 and ISO 27018 in early 2024. The ISO 27017 certification demonstrates cloud service security to users, while the ISO 27018 certification ensures that personal data is processed securely, further boosting customers confidence. Additionally, 2-factor authentication can be implemented as option, and our yearly penetration test added as extra bonus for customers. 



HR analytics is the collection and application of talent data is to improve critical talent and business outcomes. TimeTec HR Analytics enable business owners to develop data-driven insights of their talent pool, improve workforce processes and promote positive employee experience. 

Instantaneous Data Crunching & Data Visualization to provide 360° on:
- Employee statistics and profiles
- Turnover & Retention Rate 
- Salary and career path history
- Staff Performance 
- Demographic data 
- Attendance 
- Absenteeism
- Leave pattern
- Claim pattern 

The Benefits of TimeTec HR Analytics: 
1. Improve talent acquisition
2. Increases talent retention
3. Prevent workplace misconduct 
4. Increase productivity 
5. Uncover skill gaps
6. Improve employee experience 
7. Build highly engaged workplace
8. Reduce attrition rate
9. Machine learning spots the patterns that you might miss 

Why TimeTec HR Analytics?

Strong Data Governance with ISO27001, ISO 27017 & ISO27018
• 2-Factor authentication & yearly Pentest for further data security 
• Assurance of Data Quality 
• Available Web & App visualization 
• Affordable DaaS model, no setup cost 
• Fast deployment with ready templates
• Detect HR anomalies fast and efficient 
• Complete HR consolidation from all sources 
• Extendable analytics to next activities for data enrichment
• Achieve data-driven HR strategy 
• Prepare for the future:  Smart HR + AI 
 
Interested to find out more on TimeTec HR Suite and TimeTec HR Analytics, together its data governance compliances? Request your Free Demo of TimeTec HR solutions now. 

03-8070 9933     |     Email     |     www.timeteccloud.com     |     Interest Form


0 comments:

Data Governance Inherently comes along with TimeTec Parking Analytics

Thursday, February 15, 2024 TimeTec 0 Comments


The fact is 90% organizations don’t have proper Data Governance in place. Data Governance department or unit is to handle requirements from regulatory bodies but at the same time, data governance is also keeping balance between Data Asset and Liabilities. 

Data governance framework creates a single set of rules and processes for collecting, storing, and using data. In details, it consists of the policies, rules, processes, organizational structures, and technologies that are put in place as part of a governance program throughout the organization.

It’s also considering as a set of principles and practices that ensure high quality through the complete lifecycle, it’s more to business rather than technology. To implement Data Governance in an organization, normally involves the following steps:

- Identify roles and responsibilities
- Define your data domains
- Establish data workflows
- Establish data controls
- Identify authoritative data sources
- Establish policies and standards

Without a robust Data Governance or information security measures within an organization, your business is at a higher risk of security incidents, such as data breaches, cyberattacks, or insider threats, which can result in financial losses, reputational damage, and legal repercussions. 

To ensure the data governance that compliance to certain recognizable standards, organizations can incorporate ISO27001 international standard that specifies the requirements for an Information Security Management System (ISMS). Because an ISMS is a framework of policies, procedures, and controls that helps you protect your data from various risks and threats. How can you integrate ISO 27001 into your Data Governance program? 

1. Assess your current data state 
Before adopting ISO 27001, understand your current data landscape and identify the gaps and weaknesses in the data security practices by using data governance maturity model to evaluate your data capabilities and performance across different dimensions, such as data quality, data architecture, data governance roles, data policies, and data ethics. Or you can also conduct a risk assessment to identify the potential sources and impacts of data breaches, leaks, or losses. 

2. Define your scope and objectives
The scope defines the boundaries of your ISMS, such as the data types, data sources, data processes, data stakeholders, and data systems that are covered by your ISMS. The objectives are to define the expected outcomes and benefits of your ISMS, such as the level of data protection, compliance, and trust that you want to achieve. 

3. Implement your Information Security Management System (ISMS)
After defining your scope and objectives, you need to implement your ISMS according to the ISO 27001 requirements. This involves developing and documenting your data security policies, procedures, and controls that address the specific risks and challenges that you might encounter. You also need to assign roles and responsibilities for data security to your data governance team and other data stakeholders. Moreover, you need to establish mechanisms for monitoring, measuring, and reporting on your data security performance and compliance.

4. Certify and improve your ISMS
The final step is to certify and improve your ISMS. Certification is an optional but recommended process that involves an external audit by an accredited body that verifies that your ISMS meets the ISO 27001 standards. Certification can help you demonstrate your commitment and credibility to your customers, partners, regulators, and other stakeholders. Improvement is an ongoing process that involves reviewing and updating your ISMS based on the feedback, lessons learned, and best practices that you collect from your data security activities.

Data Governance for Parking Analytics 

Nowadays, organizations tend to subscribe applications from SaaS (Software as a Service) providers, the SaaS become the production plant for inputting raw data and generating meaningful data output.  It is preferable that the solution provider provides extended DaaS (Data as a Service). It would be a plus point if the solution provider complies with ISO27001 certification to ensure data quality and data governance for the solutions, allowing you to focus on business value and organizational outcomes.

Subscribing to SaaS & DaaS and ensuring data governance compliance can mitigate the risk management and data breaches, which inherently core governance components. These compliances will cover the scope related to the applications that you have subscribed to, such as TimeTec Smart Parking for your day-to-day operation. 

For your information, TimeTec has been ISO27001 certified organization since 2018 and enhanced with ISO 27017 and ISO 27018 in early 2024. The ISO 27017 certification demonstrates cloud service security to users, while the ISO 27018 certification ensures that personal data is processed securely, further boosting customers confidence. Additionally, 2-factor authentication can be implemented as option, and our yearly penetration test added as extra bonus for customers. 


TimeTec Parking is the one-stop parking solution provider capable of fulfilling the most sophisticated parking requirements and facilitating further activities to form a smart building ecosystem. TimeTec Parking Analytics offers instantaneous data crunching and data visualization, providing a 360° view on:

- Collection breakdown by duration
- Single view and overview
- Earnings per vehicle
- Earnings per bay
- Occupancy rate
- Season Pass turnover rate
- Income per site analytics
- User behavior analysis
- Different parking methods and next activities
- And many more

For example, for bay utilization, an operator can plan their bays especially the mix ratio of casual and season parking bays properly if they know the details clearly to optimize the bay utilization and maximize the profits.   

The Benefits:
1. Increase parking occupancy based on user behavior
2. Maximize parking revenue streams by right-sizing product offerings
3. Identify dynamic pricing opportunities that enhance your parking strategy
4. Make period-over-period comparisons
5. Identify successes and pinpoint areas for improvement

Why TimeTec Parking Analytics? 

• Strong Data Governance with ISO27001, ISO27017 & ISO27018
• 2-Factor authentication & yearly Pentest for further data security 
• Assurance of Data Quality 
• Available Web & App visualization 
• Affordable DaaS model, no setup cost 
• Fast deployment with ready templates
• Detect HR anomalies fast and efficient 
• Complete HR consolidation from all sources 
• Extendable analytics to next activities for data enrichment
• Achieve data-driven HR strategy 
• Prepare for the future:  Smart HR + AI 

Interested in learning more about TimeTec Parking Analytics and TimeTec Parking? Request your free demo of the TimeTec Parking solution now.

03-8070 9933     |     Email     |     www.timeteccloud.com     |     Interest Form
 

0 comments:

Data Governance Inherently comes along with iNeighbour Analytics

Thursday, February 15, 2024 TimeTec 0 Comments


The fact is 90% organizations don’t have proper Data Governance in place. Data Governance department or unit is to handle requirements from regulatory bodies but at the same time, data governance is also keeping balance between Data Asset and Liabilities. 

Data governance framework creates a single set of rules and processes for collecting, storing, and using data. In details, it consists of the policies, rules, processes, organizational structures, and technologies that are put in place as part of a governance program throughout the organization.

It’s also considering as a set of principles and practices that ensure high quality through the complete lifecycle, it’s more to business rather than technology. To implement Data Governance in an organization, normally involves the following steps:

- Identify roles and responsibilities
- Define your data domains
- Establish data workflows
- Establish data controls
- Identify authoritative data sources
- Establish policies and standards

Without a robust Data Governance or information security measures within an organization, your business is at a higher risk of security incidents, such as data breaches, cyberattacks, or insider threats, which can result in financial losses, reputational damage, and legal repercussions. 

To ensure the data governance that compliance to certain recognizable standards, organizations can incorporate ISO27001 international standard that specifies the requirements for an Information Security Management System (ISMS). Because an ISMS is a framework of policies, procedures, and controls that helps you protect your data from various risks and threats. How can you integrate ISO 27001 into your Data Governance program? 

1. Assess your current data state 
Before adopting ISO 27001, you can understand your current data landscape and identify the gaps and weaknesses in the data security practices by using data governance maturity model to evaluate your data capabilities and performance across different dimensions, such as data quality, data architecture, data governance roles, data policies, and data ethics. Or you can also conduct a risk assessment to identify the potential sources and impacts of data breaches, leaks, or losses. 

2. Define your scope and objectives
The scope defines the boundaries of your ISMS, such as the data types, data sources, data processes, data stakeholders, and data systems that are covered by your ISMS. The objectives are to define the expected outcomes and benefits of your ISMS, such as the level of data protection, compliance, and trust that you want to achieve. 

3. Implement your Information Security Management System (ISMS)
After defining your scope and objectives, you need to implement your ISMS according to the ISO 27001 requirements. This involves developing and documenting your data security policies, procedures, and controls that address the specific risks and challenges that you might encounter. You also need to assign roles and responsibilities for data security to your data governance team and other data stakeholders. Moreover, you need to establish mechanisms for monitoring, measuring, and reporting on your data security performance and compliance.

4. Certify and improve your ISMS
The final step is to certify and improve your ISMS. Certification is an optional but recommended process that involves an external audit by an accredited body that verifies that your ISMS meets the ISO 27001 standards. Certification can help you demonstrate your commitment and credibility to your customers, partners, regulators, and other stakeholders. Improvement is an ongoing process that involves reviewing and updating your ISMS based on the feedback, lessons learned, and best practices that you collect from your data security activities.

Data Governance for iNeighbour Analytics 

Nowadays, organizations tend to subscribe to applications from SaaS (Software as a Service) providers. SaaS has become the production plant for inputting raw data and generating meaningful data output. It is preferable for the solution provider to offer extended DaaS (Data as a Service). It would be a plus point if the solution provider complies with ISO 27001 certification to ensure data quality and governance for the particular solutions, allowing you to focus on business value and organizational outcomes.

Subscribing to SaaS & DaaS and ensuring data governance compliance can mitigate risk management and data breaches, which are inherently core governance components. These compliances will cover the scope related to the applications you have subscribed to, such as the TimeTec iNeighbour Smart Residential System for your day-to-day residential management.

For your information, TimeTec, the owner of iNeighbour, has been ISO 27001 certified since 2018 and enhanced with ISO 27017 and ISO 27018 in early 2024. The ISO 27017 certification demonstrates cloud service security to users, while the ISO 27018 certification ensures that personal data is processed securely, further boosting customer confidence. Additionally, 2-factor authentication can be implemented as an option, and our yearly penetration test is an extra bonus for customers.


iNeighbour Analytics is available as an optional module for the iNeighbour super app, allowing JMB/JMC/MC/RA/Developers to continue the data journey, saving costs and time without the hassle and need for extensive data lifecycle measures mentioned earlier to maintain data quality. Data quality flows intuitively in a lineage form along with the applications, providing readily prepared templates for easy visualization and benchmark references.

By logging into iNeighbour Analytics, JMB/JMC/MC/RA/Developers and management can obtain a clear picture of their neighborhood activities overview and a single view easily in multiple presentation formats on the web and app, providing all the essentials for building management to improve the health of their property management and better portfolio of their owners and tenants.

iNeighbour Analytics offers instantaneous data crunching and data visualization, providing a 360° view on:

• Units and user analytics 
• Occupancy rates 
• Accounting analytics 
• Outstanding debt analytics 
• Facility booking analytics
• Visitors analytics 
• Patrol management analytics 
• E-info, e-Form analytics 
• Maintenance analytics 
• Parking analytics 
• Feedback/Inquiry analytics 
• Admin KPI 
• Many more

The Benefits:
- Increase unit owners' and tenants' satisfaction
- Detect and remedy blind spots easily
- Better accounting control
- More accurate advice on tenants and residents
- Enhance neighborhood security
- Review and improve property management
- Informed decision-making driven by data
- Boost property value

Why TimeTec iNeighbour Analytics? 

• Strong Data Governance with ISO27001, ISO 27017 & ISO27018
• 2-Factor authentication & yearly Pentest for further data security 
• Assurance of Data Quality 
• Available Web & App visualization 
• Affordable DaaS model, no setup cost 
• Fast deployment with ready templates
• Detect property management anomalies fast and efficient 
• Complete property management activities data consolidation from all sources 
• Extendable analytics to next activities for data enrichment
• Achieve data-driven property management strategy 
• Prepare for the future:  Smart community + AI 

Interested in learning more about iNeighbour Analytics and iNeighbour? Request your free demo of the iNeighbour Residential Property Management solution now.

03-8070 9933     |     Email     |     www.timeteccloud.com     |     Interest Form

0 comments:

Data Quality Intuitively comes along with TimeTec Parking Analytics

Friday, February 09, 2024 TimeTec 0 Comments


The quality of data is a prerequisite for a meaningful data analytics deployment. Characteristics of Data Quality are accuracy, completeness, consistency, uniqueness, and timeliness. Without Data Quality, data analytics process might paint a false picture and risking the companies to make wrong decision. 

The few elements contribute to Data Quality:

Accuracy: a company has to cross-check data with the source. If there is no data lineage, the accuracy is always questionable. 

Completeness: It doesn’t mean all data source, but it must adhere to the business requirements, especially those data is used for KPI measurement. 

Consistency: If data is flowed to multiple applications, it must have the same properties and not conflicting each other. For example, if the date format is DDMMYYYY,  make sure it should be the same across all applications. 

Validity: It should follow the business rules and parameters. For example, if the amount rounds up after 2 decimals, then it should.  

Uniqueness: There must be no duplication of data. 

Timelines: Data must be available when promised. 

There are quite some methods suggested by data experts to improve Data Quality, among them: Data Profiling, Data Standardization, Data Geocoding, Data Matching and Linking, and Data Quality Monitoring. 


To ensure Data Quality is kept, organizations have to maintain a Data Life Cycle, which involves the processes:

1. Find data through root cause analysis
2. Investigate data
3. Find potential causes
4. Perform root cause analysis
5. Apply correction
6. Monitor by continuous improvement monitoring
7. Sustain by applying fixes on sources or closest to source



Hence, to achieve Data Driven Organization is easier said than done. Since data itself generates further data, especially when raw data go into applications generate and regenerate much meaningful data, solution providers who have the capability to provide data analytics services should be the better choices for companies that take data seriously and have the plan for data transformation. 

The complication of parking operations arises from multiple parking types, such as casual parking, season parking, on-street parking, valet parking, event parking, etc., and multiple payment methods like cash and cashless transactions, which include credit cards, debit cards, Touch ‘n Go, eWallets, FPX, offline, and online payments, across various parking sites. This complexity worsen the data quality when need to consolidate multiple parking and payment methods provided by different solution providers. 


TimeTec Parking is the one-stop parking solution provider capable of fulfilling the most sophisticated parking requirements and facilitating further activities to form a smart building ecosystem. Additionally, TimeTec Parking Analytics is available as an optional module for TimeTec Parking, allowing parking operators to continue the data journey, saving costs and time without the hassle and the need for extensive data lifecycle measures mentioned earlier to maintain data quality. The data quality flows intuitively in a lineage form along with the applications, providing readily prepared templates for easy visualization and benchmark reference.

TimeTec Parking Analytics offers instantaneous data crunching and data visualization, providing a 360° view on:

Collection breakdown by duration
Single view and overview
Earnings per vehicle
Earnings per bay
Occupancy rate
Season Pass turnover rate
Income per site analytics
User behavior analysis
Different parking methods and next activities
And many more

For example, for bay utilization, an operator can plan their bays especially the mix ratio of casual and season parking bays properly if they know the details clearly to optimize the bay utilization and maximize the profits.   

The Benefits:
1. Increase parking occupancy based on user behavior
2. Maximize parking revenue streams by right-sizing product offerings
3. Identify dynamic pricing opportunities that enhance your parking strategy
4. Make period-over-period comparisons
5. Identify successes and pinpoint areas for improvement

Interested in learning more about TimeTec Parking Analytics and TimeTec Parking? Request your free demo of the TimeTec Parking solution now.

03-8070 9933     |     Email     |     www.timeteccloud.com     |     Interest Form

0 comments:

Data Quality Intuitively comes along with iNeighbour Analytics

Friday, February 09, 2024 TimeTec 0 Comments


The quality of data is a prerequisite for a meaningful data analytics deployment. Characteristics of Data Quality are accuracy, completeness, consistency, uniqueness, and timeliness. Without Data Quality, data analytics process might paint a false picture and risking the companies to make wrong decision. 

The few elements contribute to Data Quality:

Accuracy: a company has to cross-check data with the source. If there is no data lineage, the accuracy is always questionable. 

Completeness: It doesn’t mean all data source, but it must adhere to the business requirements, especially those data is used for KPI measurement. 

Consistency: If data is flowed to multiple applications, it must have the same properties and not conflicting each other. For example, if the date format is DDMMYYYY,  make sure it should be the same across all applications. 

Validity: It should follow the business rules and parameters. For example, if the amount rounds up after 2 decimals, then it should.  

Uniqueness: There must be no duplication of data. 

Timelines: Data must be available when promised. 

There are quite some methods suggested by data experts to improve Data Quality, among them: Data Profiling, Data Standardization, Data Geocoding, Data Matching and Linking, and Data Quality Monitoring. 



To ensure Data Quality is kept, organizations have to maintain a Data Life Cycle, which involves the processes:

1. Find data through root cause analysis
2. Investigate data
3. Find potential causes
4. Perform root cause analysis
5. Apply correction
6. Monitor by continuous improvement monitoring
7. Sustain by applying fixes on sources or closest to source


Hence, to achieve Data Driven Organization is easier said than done. Since data itself generates further data, especially when raw data go into applications generate and regenerate much meaningful data, solution providers who have the capability to provide data analytics services should be the better choices for companies that take data seriously and have the plan for data transformation. 

Technological advancements that consolidate all activities into a single super app in recent years are aiding residential property management in its digital transformation journey. TimeTec is the prominent smart community solution provider capable of fulfilling the most sophisticated residential property management needs through its iNeighbour super app, and now furthering the journey on data transformation.

iNeighbour Analytics is available as an optional module for the iNeighbour super app, allowing JMB/JMC/MC/RA/Developers to continue the data journey, saving costs and time without the hassle and need for extensive data lifecycle measures mentioned earlier to maintain data quality. Data quality flows intuitively in a lineage form along with the applications, providing readily prepared templates for easy visualization and benchmark references.


By logging into iNeighbour Analytics, JMB/JMC/MC/RA/Developers and management can obtain a clear picture of their neighborhood activities overview and a single view easily in multiple presentation formats on the web and app, providing all the essentials for building management to improve the health of their property management and better portfolio of their owners and tenants.

iNeighbour Analytics offers instantaneous data crunching and data visualization, providing a 360° view on:

• Units and user analytics 
• Occupancy rates 
• Accounting analytics 
• Outstanding debt analytics 
• Facility booking analytics
• Visitors analytics 
• Patrol management analytics 
• E-info, e-Form analytics 
• Maintenance analytics 
• Parking analytics 
• Feedback/Inquiry analytics 
• Admin KPI 
• Many more

The Benefits:
- Increase unit owners' and tenants' satisfaction
- Detect and remedy blind spots easily
- Better accounting control
- More accurate advice on tenants and residents
- Enhance neighborhood security
- Review and improve property management
- Informed decision-making driven by data
- Boost property value

Interested in learning more about iNeighbour Analytics and iNeighbour? Request your free demo of the iNeighbour Residential Property Management solution now.

03-8070 9933     |     Email     |     www.timeteccloud.com     |     Interest Form

0 comments:

Data Quality Intuitively comes along with TimeTec HR Analytics

Friday, February 09, 2024 TimeTec 0 Comments


The quality of data is a prerequisite for a meaningful data analytics deployment. Characteristics of Data Quality are accuracy, completeness, consistency, uniqueness, and timeliness. Without Data Quality, data analytics process might paint a false picture and risking the companies to make wrong decision. 

The few elements contribute to Data Quality:

Accuracy: a company has to cross-check data with the source. If there is no data lineage, the accuracy is always questionable. 

Completeness: It doesn’t mean all data source, but it must adhere to the business requirements, especially those data is used for KPI measurement. 

Consistency: If data is flowed to multiple applications, it must have the same properties and not conflicting each other. For example, if the date format is DDMMYYYY,  make sure it should be the same across all applications. 

Validity: It should follow the business rules and parameters. For example, if the amount rounds up after 2 decimals, then it should.  

Uniqueness: There must be no duplication of data. 

Timelines: Data must be available when promised. 

There are quite some methods suggested by data experts to improve Data Quality, among them: Data Profiling, Data Standardization, Data Geocoding, Data Matching and Linking, and Data Quality Monitoring. 


To ensure Data Quality is kept, organizations have to maintain a Data Life Cycle, which involves the processes:

1. Find data through root cause analysis
2. Investigate data
3. Find potential causes
4. Perform root cause analysis
5. Apply correction
6. Monitor by continuous improvement monitoring
7. Sustain by applying fixes on sources or closest to source



Hence, to achieve Data Driven Organization is easier said than done. Since data itself generates further data, especially when raw data go into applications generate and regenerate much meaningful data, solution providers who have the capability to provide data analytics services should be the better choices for companies that take data seriously and have the plan for data transformation. 

TimeTec HR Analytics comes as an option module for TimeTec HR suite, for companies to continue to complete the data journey to save cost and time, without the pains and the needs of hassle and data life cycle measures as mentioned above to upkeep the data quality. The data quality flows intuitively in a lineage form along with the applications to readily prepared templates for easy visualization and benchmarks reference. 

HR analytics is the collection and application of talent data is to improve critical talent and business outcomes. TimeTec HR analytics enable business owners to develop data-driven insights of their talent pool, improve workforce processes and promote positive employee experience.



Instantaneous Data Crunching & Data Visualization to provide 360° on:
- Employee statistics and profiles
- Turnover & Retention Rate 
- Salary and career path history
- Staff Performance 
- Demographic data 
- Attendance 
- Absenteeism
- Leave pattern
- Claim pattern 




The Benefits of TimeTec HR Analytics: 
1. Improve talent acquisition
2. Increases talent retention
3. Prevent workplace misconduct 
4. Increase productivity 
5. Uncover skill gaps
6. Improve employee experience 
7. Build highly engaged workplace
8. Reduce attrition rate
9. Machine learning spots the patterns that you might miss 

Interested to know more about TimeTec HR Analytics and TimeTec HR Suite? Request your Free Demo of TimeTec HR solutions now. 


03-8070 9933     |     Email     |     www.timeteccloud.com     |     Interest Form

0 comments:

Differentiating Dashboards and Analytics for Informed Business Decisions

Friday, January 26, 2024 TimeTec 0 Comments

 
Lots of solution providers use the system dashboard that comes along with their solutions as data analytics module to deceive customers. In fact, data analytics is much more than that.

In brief, a dashboard is a visual display of key performance indicators (KPIs) and other relevant information, presented in a consolidated and easy-to-understand format. It provides a real-time snapshot of data and helps users monitor and make decisions based on that data. In short, dashboard is more for operational.  

On the other hand, data analytics involves the process of examining raw data to extract insights, identify patterns, and make informed conclusions. It goes beyond visualization to explore data trends, correlations, and anomalies, often using statistical and machine learning techniques. In short, data analytics is more for management to understand in-depth situation and to enhance operation, but more importantly to make strategical decision that would affect the future of the organization.  


In terms of benefits, Dashboards may deliver the followings:

1. Real-time Monitoring:
Dashboards provide a real-time overview of key metrics, enabling quick and informed decision-making as you can track operational performance instantly.

2. Visual Representation:
Visual elements like charts and graphs make it easier to comprehend complex data. Dashboards condense large amounts of information into a visually digestible format.

3. User-Friendly:
Dashboards are designed for ease of use, making them accessible to a broad audience within an organization. Users can quickly grasp trends and performance without needing in-depth data analysis skills.

4. Efficiency:
Dashboards save time by providing a consolidated view, eliminating the need to sift through extensive reports. This promotes efficiency in operational decision-making processes.

And for Data Analytics, it delivers different types and more impactful benefits to the businesses:

1. In-Depth Analysis:
Data analytics allows for a deeper exploration of data, uncovering patterns, trends, and insights that might not be immediately apparent on a dashboard.

2. Predictive Modeling:
Advanced analytics, including machine learning, enables predictive modeling. Organizations can forecast future trends and make proactive decisions based on these predictions.

3. Data-driven Decision Making:
Analytics provides a robust foundation for making strategic decisions. By relying on data rather than intuition, organizations can enhance decision accuracy when planning the future moves.

4. Identification of Opportunities and Risks:
Analytics helps in identifying both opportunities for growth and potential risks by analyzing historical and current data. This proactive approach supports better risk management.

5. Continuous Improvement:
Analytics fosters a culture of continuous improvement. By regularly analyzing data, organizations can refine strategies, optimize processes, and stay agile in response to changing conditions.

In summary, they complement each other; dashboards are excellent for quick, visual insights and monitoring, while data analytics requires more expertise to offer an in-depth exploration of data, supporting strategic decision-making and long-term planning.

TimeTec solutions, be it HR suite, property management, smart security, and smart parking, the applications all come with dashboards on their own to help customers in quick visual performance for operation. While we provide TimeTec Analytics modules across platforms, customizable and consolidated in an ecosystem, it allows management to access anytime, anywhere on the web or on the app without the need to log into their individual operation system, to obtain deeper analysis and interpretation of data for actionable insights.


 
 About TimeTec:
TimeTec Group was established in 2000. Over the past 20 years, the Group has developed three homegrown, globally recognized IT brands: FingerTec, TimeTec, and iNeighbour. These brands specialize in workforce management, security, smart parking, smart office, smart residential, and smart township solutions, harnessing the power of biometrics, cloud and edge computing, IoT, and AI technologies. All these solutions connect and reshape the landscape of work life and home life within a larger ecosystem.

Through an extensive network, TimeTec Group distributes its biometric hardware products and 18 cloud applications, including IoT devices, to more than 150 countries worldwide. Visit our company websites at TimeTec Cloud, FingerTec, iNeighbour, and TimeTec Building.

Various renowned clients have subscribed to TimeTec's solutions, including IOI Properties, Putrajaya Holdings, Ibraco, Binastra, Thriven, Hock Seng Lee, QSR Brands, Central Sugars Refinery (CSR), Sunway Constructions, Mamee, Yakult, Nano Malaysia Berhad, and many more. The versatility and feasibility of TimeTec products also attract international customers from around the world, including Hong Kong, Dubai, Australia, South Africa, and beyond.

03-8070 9933     |     Email     |     www.timeteccloud.com     |     Interest Form

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Fusionex’s Downfall: The End of the Big Data Era?

Monday, January 22, 2024 TimeTec 0 Comments


The largest big data company in Malaysia, Fusionex, is set to be liquidated by its new buyer Hitachi through a court order. Financial data analysis from a YouTuber, Learnabee video reveals that despite "steady growth" in performance and profits, Fusionex is experiencing a precipitous decline in cash flow. Additionally, since Fusionex's revenue is primarily driven by projects, resorting to the strategy of capitalizing expenses to artificially enhance the financial outlook is not advisable. Instead of reporting profits, it would be more realistic to acknowledge losses in each of the three years following the acquisition by Hitachi.

Nevertheless, why did Fusionex collapse? Is the big data industry failing? Wasn't it said that AI is built on the foundation of big data? How did big data companies decline just as Large Language Model (LLM) gained popularity? Where does this logic fit?

Based on my personal understanding and observations of the industry, I'll outline the reasons behind Fusionex's closure.

The popularity of big data arises from the increasing volume of data produced by individuals and businesses every day. Previously, data generation was inconvenient and costly. For instance, writing a diary used to be a rare habit, and it was done manually in a book with limited circulation. Now, diary writing is a common practice, especially on social media platforms. Previously, people used cash, making it difficult to track transactions. Now, with the rise of ewallets, every transaction leaves a trace. Similarly, businesses produce more data due to digitalization, and those who understand how to convert it into valuable insights and actions can add significant value to their operations. Companies lacking in-house data talent seek external assistance, giving rise to big data firms like Fusionex.

If big data is so crucial, why did Fusionex's prospects deteriorate to the point of the owner selling it off? While selling a company may be due to a favorable offer rather than concerns about its future, incidents that exposed three years later for Fusionex suggest otherwise. While this might be seen as a case of poor management, my view is different; I see it as an inherent flaw in the industry.

Firstly, internet giants, the pioneers where the concept of big data originated, are the best equipped to engage in discussions about big data, treating data as their most valuable asset. They establish internal data teams ranging from dozens to thousands of professionals who continuously analyze, utilize, and cultivate data. Occasional consultations with external experts are the exception, as these companies rarely seek outsourcing for big data services. Can you imagine Google, Facebook, Alibaba, or JD outsourcing their big data analytics to external firms?

Secondly, even if traditional large enterprises lack the expertise in big data and initially rely on services from companies like Fusionex, this is usually temporary. Data is a trade secret, and once these enterprises establish their own data teams after gaining experience, they tend to recruit the talent responsible for their projects from the outsourcing company. I believe Fusionex's primary clients were these traditional enterprises or government departments, and they are prone to being phased out, especially after a change in government.

Thirdly, to achieve data-driven decision-making, digitization must precede datafication, and this relies on application systems. More and more system providers are contemplating integrating data analysis modules into their systems as part of their products, assisting clients in transitioning seamlessly from digitization to datafication. System providers with data analytics capability have an extra advantage of industry know-how over big data companies. This advantage reduces costs and time for enterprises, sidelining specialized big data companies. TimeTec, which launched the data analytics modules for all its solutions last year after two years of development, was one of the moves to prove such a trend.

In essence, what was once exclusive to a few has now become commonplace. While big data's importance continues to grow, the significance of big data companies appears to be diminishing.

 
About Author:
Teh Hon Seng is the Founder and Group CEO of TimeTec Group of Companies. Prior to founding TimeTec, Teh led his former company to be listed on the MESDAQ (ACE) market of Bursa Malaysia in 2002. In 2000, Teh initiated research and development in fingerprint technology, which later evolved into a renowned global brand for commercial fingerprint products known as FingerTec. In 2008, he foresaw the trends of cloud computing and mobile technology. Over the years, he strategically diversified and transformed his biometric-focused products into a suite of cloud solutions aimed at workforce management and security industries, including smart communities and digital building systems centered around the cloud ecosystem. Teh holds more than 20 patents, and he has also been a columnist in a local newspaper and the author of several books.
 
 About TimeTec:
TimeTec Group was established in 2000. Over the past 20 years, the Group has developed three homegrown, globally recognized IT brands: FingerTec, TimeTec, and iNeighbour. These brands specialize in workforce management, security, smart parking, smart office, smart residential, and smart township solutions, harnessing the power of biometrics, cloud and edge computing, IoT, and AI technologies. All these solutions connect and reshape the landscape of work life and home life within a larger ecosystem.

Through an extensive network, TimeTec Group distributes its biometric hardware products and 18 cloud applications, including IoT devices, to more than 150 countries worldwide. Visit our company websites at TimeTec Cloud, FingerTec, iNeighbour, and TimeTec Building.

Various renowned clients have subscribed to TimeTec's solutions, including IOI Properties, Putrajaya Holdings, Ibraco, Binastra, Thriven, Hock Seng Lee, QSR Brands, Central Sugars Refinery (CSR), Sunway Constructions, Mamee, Yakult, Nano Malaysia Berhad, and many more. The versatility and feasibility of TimeTec products also attract international customers from around the world, including Hong Kong, Dubai, Australia, South Africa, and beyond.

03-8070 9933     |     Email     |     www.timeteccloud.com     |     Interest Form

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