Recent developments in artificial intelligence (AI) and machine learning (ML) have profoundly impacted data analytics, allowing for informed, real-time decision-making and improved strategy execution. As interest in data analytics among C-suite executives increases, it is crucial to understand how it can be used to empower strategy and performance management.

The KPI Institute, a leading global research institute specialized in business performance, is proud to announce the publication of the 26th issue of Performance Magazine, which goes on a deep dive into how data analytics is being used to transform the way companies operate, develop business strategies, and manage performance. This issue also includes best practices and case studies on integrating innovative technologies such as AI and ML into an organization’s operations. 

Our cover story features insights from Madhur Mayank Sharma, senior director and head of AI development at SAP Asia PTE LTD, who shared his thoughts on how to develop a forward-thinking, dynamic data strategy. In addition, we also feature a plethora of experts in the field of data analytics, each of whom has provided a unique perspective on how organizations can create a data strategy and establish a data-driven culture.

Furthermore, our very own experts from The KPI Institute provided answers to questions on data analytics, such as:

• How can organizations bridge the knowledge gap between data analysts and nontechnical stakeholders and decision-makers?
• How can managers and executives stay up-to-date with the latest advancements in data analytics?
• What are the most important KPIs for measuring the ROI of data analytics initiatives?

This issue also includes in-depth articles on topics such as how to leverage data for sustainability strategies, how to use business simulations to practice decision-making and problem-solving skills, how to identify whether or not the data gathered is of “good” quality, and how businesses can avoid falling prey to hype by adopting technologies that actually matter. 

Aspiring data analytics professionals will also learn a lot from our Career Insights section, which features an article detailing the importance of building a strong statistical foundation. Readers can also peruse our recommended resources, which include books, podcasts, webinars, and more.

Ensure your organization doesn’t fall behind on the latest data analytics trends impacting business, strategy, and performance management by checking out the latest issue of Performance Magazine today! You can get a digital version via the TKI Marketplace or order a printed copy from Amazon.

In a mission to equip professionals with the skills and knowledge for navigating today’s business landscape, The KPI Institute joins forces with maentae, a progressive learning solution provider, to develop a course on harnessing the power of artificial intelligence (AI).

AI for Business Productivity online course, which is expected to launch this year, will offer participants the opportunity to learn the practical application of several AI tools to optimize various business functions guided by key learning objectives, including:

• Gain a good understanding of the different use cases and applications of AI in business, including marketing, customer service, sales, operations, HR, and innovation
• Learn how to identify the opportunities to adopt AI in your business
• Learn how to integrate AI tools into your business 
• Enhance your career prospects by acquiring in-demand skills in AI and demonstrating your ability to drive productivity and growth
• Connect and interact with a community of like-minded professionals, looking to deepen their knowledge in emerging technologies, as well as expand their network and career opportunities

Throughout the course, participants will get access to real-world case studies and examples showcasing successful applications of AI in numerous industries and business functions as well as interactive modules with practical exercises.

This course features several  lessons covering various topics and business functions, such as marketing, sales, operations, customer relations, and human resources. The modules consist of specific use cases for AI tools and hands-on training to ensure participants will learn how to integrate the tools into business functions, and the overall business operations.

The KPI Institute, with 19 years of experience in providing solutions for performance excellence, invites decision-makers, stakeholders, business owners, and entrepreneurs to future-proof their businesses and increase adaptability.

maentae’s goal is to empower individuals at every skill level to thrive in the dynamic and ever-changing modern workforce. Its core values focus on the combination of science, art and technology—crafting curricula that transcend boundaries with a harmonious blend of academic research and practical insights.

Participants who complete the course will be awarded a certificate in AI for Business Productivity, which they can use to prove their knowledge and proficiency in using AI to boost efficiency and productivity in business. Get updates on the launch of the course by visiting the TKI Marketplace, or contact Alexandru Muntean, head of customer engagement: [email protected] +40 747 060 997.

In the previous article, Linh Do,  Head of Professional Services at The KPI Institute Vietnam, highlights the geopolitical, environmental, and economic challenges that impact Southeast Asia. Understanding these factors is crucial for grasping the local dynamics and uncovering regional growth opportunities. In this article, Linh will delve into potential measures that can be implemented to enhance performance management in the region. 

Improving performance management in Southeast Asia involves diversifying their supplier base, investing in innovation, enforcing sustainable practices, leveraging AI technologies, and upskilling employees.

Implement risk management strategies. To mitigate the further impact of global recession and trade disruption, companies should pay attention to risk management in planning their strategy and manage them accordingly. This begins with implementing proactive risk assessment measures to identify potential threats that might negatively affect their business and the weaknesses within their operation that might strengthen those impacts. Subsequently, companies can employ various remedies to address these vulnerabilities. Organizations can secure a steady supply of raw materials by evaluating alternative sourcing options, establishing backup suppliers, and exploring local or regional partnerships while mitigating the risks associated with production delays and cost fluctuations.

Capture and manage the impacts on ESG-related matters. Businesses will need to manage this aspect through effective strategy planning associated with performance management practices, such as setting objectives to identify opportunities for sustainable business growth, reduce carbon footprints, and implement sustainable supply chain practices. Some KPIs to consider may include # Initiatives to promote environmental responsibility,  % Current production lines that are environmentally friendly, and % Energy produced from renewable sources.

Adjust performance management practices to stay productive in the new work arrangement. To ensure remote workers remain engaged and productive while maintaining a sense of connectedness and collaboration with colleagues, companies like Lazada have implemented remote work policies, providing online training programs and running digital Employees Net Promoter Score surveys to support their engagement and professional development. In addition, companies should move the focus from measuring process KPIs such as # Work hour to finish a task to more output and value-oriented KPIs such as # Tasks done on time that meet the requirements.

Utilize new technologies effectively. An excellent example of this is companies like Grab and DBS Bank have implemented AI technologies to streamline operations and improve customer experiences. To succeed in AI implementation, companies need clear performance metrics. Depending on their goals, such as cost reduction or lead time improvement, relevant KPIs can be used, like % cost saved or # lead time using AI technology.

Identifying the optimal approach to maintain resilience in this highly dynamic environment is challenging, yet managing them to ensure relevancy and effectiveness is even more arduous. Therefore, it is important to equip yourself with comprehensive knowledge and skills to facilitate these processes. 

Elevate your competitive edge by enrolling in The KPI Institute’s Certified Strategy and Business Planning Professional and Certified Performance Management Professional courses, allowing you to gain insights into these subjects and maintain a leading position in your field.

Editor’s Note: “Four Business Intelligence Trends in 2022” is an article written by The KPI Institute’s Research Analyst, Brian Kiprop. This piece is originally published in the 22nd Performance Magazine – Printed Edition.

As the year progresses, entrepreneurs and managers are developing growth strategies as they establish data-driven cultures in their companies. Business intelligence assists in making data-driven decisions by utilizing data infrastructure, tools, and best practice benchmarks. Many businesses can identify new opportunities by having a wide view and utilization of data. This could spark change, eradicate inefficiencies, and adjust to market changes.

To determine the trending scientific business intelligence concepts for 2022, we conducted secondary research by collecting recent publications from the Scopus engine, the largest database of highly influential scientific publications. In 2022, there are 45 documents from a range of disciplines; computer science (28), Engineering (22), Decision Sciences (11), Social Sciences (11), Mathematics (6), Business and Management (5), Energy (2), Materials Science (2), and Biochemistry and Molecular Biology (1). 

Since all 45 documents have been published this year in well-recognized journals like Springer and Emerald, we exported the data for analysis to the latest version of Voss viewer software released this year. Voss viewer software is a data visualization tool developed at the Center for Science and Technology Science at Leiden University. 

Our results from a keyword analysis show four keywords (concepts) predominant in up-to-date publications of business intelligence by researchers in 2022. They include business intelligence, information analysis, artificial intelligence, and decision making. 

Business Intelligence

As a standalone concept and the most occurring keyword (32 instances) in our research, business intelligence is an attractive area of interest for businesses and researchers. Business intelligence enables companies to make fast decisions by understanding historical and current data in a business context. These will promote better performance, assess customer behavior patterns, analyze competitors, and identify market opportunities. 

When designing business intelligence tools, IBM suggests that companies adopt an easy-to-operate business intelligence analytical solution, integrating data sources from different platforms and understanding capabilities like artificial intelligence and machine learning before implementation. 

Microsoft uncovers four stages that business intelligence undergoes, from raw data to reports and insights. Step 1 involves data collection, followed by spotting patterns in the data. The third step focuses on visualizing the data, while the last step concerns taking action on findings in real time. 

Information Analysis

The information analysis concept has 16 occurrences across our literature review. Information analysis is known to be part and parcel of intelligence gathering to influence firm decisions. After gathering the business data, assessing data sets to provide insights is crucial for deciding the actions to take from them. Data can then be processed using a different range of tools, and some of the major software are Microsoft Power BI and Tableau. 

The tools for data analysis usually consisted of dashboards, visualizations, data mining, Extract Transfer Load, reporting, and Online Analytical Processing. However, the most popular among users are visualizations and dashboards.

Artificial Intelligence 

Artificial intelligence refers to systems and machines that draw knowledge from previous experiences, adapt fresh inputs, and conduct human-like activities. In our study, we found artificial intelligence to have four keyword occurrences. 

According to Harvard Business Review, three types of Artificial Intelligence relate to solving business needs. The first one, process automation, enables administrative tasks like data transfer through emails to be updated in the recording system. The second is cognitive insight, which utilizes algorithms to determine patterns in large amounts of data and generate insights. Lastly, cognitive engagement comprises intelligent agents and chatbots that respond to customer inquiries. 

Decision Making

In our findings, decision-making had a keyword occurrence of five across all 45 papers. Decision-making is an essential outcome of collecting business intelligence. Many companies want to make better decisions concerning their strengths, weaknesses, opportunities, and threats within their business environment. 

In Minggao Yang’s paper on the influence of business intelligence on the financial performance of innovative companies, the author finds a direct correlation between business intelligence and business performance, thereby confirming that data-driven choices influence business profitability positively.

Managers and founders looking into expanding business intelligence capabilities to identify and act on sustainable and profitable opportunities could benefit from understanding the four emerging concepts in business intelligence. As collecting business intelligence requires basic skills in analyzing data, one can consider taking The KPI Institute’s Certification in Data Analysis to build or upgrade their data analysis skills.

Editor’s Note: “Business Analytics Trends: Is the Future of Data Here?” is an article written by Islam Salahuddin and originally published in the latest edition of Performance Magazine. 

Machines don’t have a worldview, according to the famous translator Richard Pevear. That’s no longer the case today, especially with data analytics. Businesses turn to data analytics to survive and adapt to disruptions. At the same time, data analytics is evolving to meet the new challenges. Here’s a glimpse of how the already noticeable trends in the pre-pandemic world have accelerated and transformed data analytics in different ways.

External Data: Predicting the Demand for Hershey’s Bars 

External data is data collected and provided by third parties. Companies now need to incorporate data from the outside world to weigh external factors in their analytics. Examples of external data are trending narratives, real-time financial trends, and property values.

In a July 2021 article, FoodDive showed how the chocolate company Hershey used data generated by IRI, a global market insights and analytics provider, to predict the demand for Hershey’s six-bar product. Since Hersey knows the number of people who plan to make s’mores in their backyards, want to spend time with family and friends, and invest in their homes during the pandemic, the manufacturer is able to adjust their inventory and production, create a relevant marketing message, and even respond to the demand for other parts of their portfolio.

Data Monetization: Where the Opportunities Are

External data can be either free or paid. While it is true that most of the datasets of the COVID-19 are available for no charge, the escalating attention to external sources could draw more attention to the paid options. According to ResearchandMarket.com’s “Global Data Monetization Platform Markets Report 2021,” data bartering, data brokering, insights bartering, and business intelligence are the four channels that shape the business processes and data evolution across the value chain.

The report states that telecommunication giants could become value-added solutions providers and offer advertising solutions through monetizing consumer data. Digital platforms and services will dominate the data monetization space while insights-as-a-service is considered “the data monetization model of the future.” Other opportunities for tech vendors and enterprises are in data security and privacy, location data, and digital data monetization platforms.

AI-empowered Analytics and Beyond

The artificial intelligence (AI)-empowered analysis of unstructured datasets is known as cognitive analytics. It depends on real-time generated data of images, videos, text, and other forms created through social media networks and the Internet of Things (IoT) technologies. It is useful in running sentiment analysis on social media interactions as it allows for better understanding of customers’ emotions and ideas and thus enables a better customer service experience.

For IoT, small-size motion sensors can now be embedded in wearable products to understand customers’ activities and needs, giving valuable insights and opening horizons for new levels of customized products.

Agile Analytics: Catch Up if You Can

However diverse your analytics methods are, they will be of no use if you do not incorporate them into operations and act on them quickly, especially during disasters. Research published in the Open Journal of Business and Management states that being agile in the analytics process involves consciousness, accessibility, decisiveness, speed, and flexibility.

In a webinar, Hugh Owen, executive vice president and chief marketing officer at the MicroStrategy, a business intelligence (BI) firm, emphasized that agile data-driven decision-making requires an organizational strategy, deploying an analytics platform in the cloud for speed, power, and security, and using self-service BI analytics to empower end users and help them save more time. 

Shifting to Cloud-based Analytics

Work from home policies have stressed the benefit of cloud analytics. Cloud storage of data means that instead of keeping data files on hardware held in the brick-and-mortar premises, data files are uploaded, kept, and governed in advanced servers operated by third-party companies, through which the data is accessed and processed.

The benefits of cloud-based analytics include reduced costs of devices required for storing and securing data, accessibility from any device, and enhanced processing speed, depending on servers’ capabilities rather than local devices. 

Scaling Up with Data Lakes 

Conversations about the rise of data lakes have been around even before the pandemic. As the volume, velocity, variety, and value of data increase and constitute big data, the need for a new form of data storage arises. A data lake is different from simple tabulated data sets like spreadsheets, arranged in defined groups called data warehouses and sometimes categorized for specific uses called data marts. A data lake is like a swamp that is able to contain raw data in structured and unstructured forms and is generated in real-time.

The importance of such capability has been emphasized by the pandemic world as more real-time data is generated, allowing for more advanced AI-driven analytics. Adopting both a data lake in addition to a data warehouse will therefore be more relevant to businesses in the post-pandemic future.

Data is essential for businesses. It helps business leaders better understand their clients, predict consumer behavior patterns, identify trends, improve the quality of services provided, and support “organizational decision-making and strategy”, according to Forbes. 

To strengthen your knowledge in developing organizational strategy and business planning using a strategic framework, join The KPI Insititute’s Certified Strategy and Business Planning Professional Live Online course on 13-17 June 2022. Visit our website for further information and sign up here.