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GenAI revolution: transforming KPIs for strategic business success

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Key performance indicators (KPIs) have been the north star guiding business strategy for decades. These criteria measure not only sales and revenue but also customer satisfaction as well as employee engagement. However, as the business landscape continues to evolve at an unprecedented pace, the need for deeper insights and more agile measurement arises. This is where the potential of generative artificial intelligence (GenAI) shines, opening doors to a new era of KPI innovation.

GenAI goes beyond automation to produce entirely novel content. It is a creative catalyst, opening up unprecedented possibilities for KPI innovation. Forget rigid, one-dimensional metrics. Powered by GenAI, KPIs become fluent, adaptive, and poetic, capturing not only the whats but also the whys and what-ifs. 

Reimagining KPIs for exponential growth

  • From static to dynamic: GenAI is capable of integrating dynamic KPIs, meaning they can evolve alongside the company that uses them. KPIs also fit seamlessly into a changing market, with trends and strategies naturally shifting along the way. 
  • Unveiling the unseen: Traditional KPIs often fail to hit the nail on the head by overlooking key, intangible factors that could affect performance. GenAI, however, can delve much deeper. With the help of GenAI, it is possible to determine brand sentiment before a particular campaign is launched, anticipate employee engagement within remote teams, or even predict customer turnover before it happens. 
  • Personalized insights, enhanced action: Data mountains no longer need to be intimidating. GenAI transforms data into personalized narratives, crafting stories tailored to individual stakeholders. Sales teams can access actionable insights, marketing managers can monitor real-time customer sentiment, and CEOs can explore what-if scenarios for strategic foresight. This data-driven storytelling fosters informed decision-making and ignites action across the organization.

A practical guide to unlocking GenAI’s potential for KPI innovation 

To effectively utilize GenAI tools like Gemini and ChatGPT for KPI innovation, follow these guidelines:

  • Define goals and challenges: Clearly articulate objectives, whether uncovering customer sentiment or anticipating market shifts.
  • Frame specific prompts: Use concise prompts such as “generate potential KPIs for measuring brand sentiment on social media.”
  • Provide relevant context: Enhance responses by furnishing background information about your industry, business model, and existing KPIs.
  • Experiment and refine: Iterate prompts, rephrase questions, and provide feedback to improve AI understanding.
  • Collaborate with experts: Involve human expertise in evaluating and implementing AI-generated insights.

While GenAI’s potential for KPI innovation is undeniable, it thrives on synergy, not substitution. The point is this: human guidance is essential. Act now, invest in your future, and become a master of the new KPI era by enrolling in The KPI Institute’s Certified KPI Professional course.

Key safety considerations for generative AI adoption in business

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In May 2023, Samsung Electronics prohibited its employees from using generative artificial intelligence (AI) tools like ChatGPT. The ban was issued in an official memo, after discovering that staff had uploaded sensitive code to the platform, which prompted security and privacy concerns for stakeholders, fearing sensitive data leakage. Apple and several Wall Street Banks have also enforced similar bans.

While generative AI contributes to increased efficiency and productivity in businesses, what makes it susceptible to security risks is also its core function: taking the user’s input (prompt) to generate content (response), such as text, codes, images, videos, and audio in different formats. The multiple sources of data, the involvement of third-party systems, and human factors influencing the adoption of generative AI add to the complexity. Failing to properly prepare for and manage security and privacy issues that come with using generative AI may expose businesses to potential legal repercussions.

Safety depends on where data is stored

So, the question becomes, how can businesses use generative AI safely? The answer resides in where the user’s data (prompts and responses) gets stored. The data storage location in turn depends on how the business is using generative AI, of which there are two main methods. 

Off-shelf tools: The first method is to use ready-made tools, like OpenAI’s ChatGPT, Microsoft’s Bing Copilot, and Google’s Bard. These are, in fact, nothing but applications with user interfaces that allow them to interact with the base technology that is underneath, namely large language models (LLMs). LLMs are pieces of code that tell machines how to respond to the prompt, enabled by their training on huge amounts of data. 

In the case of off-the-shelf tools, data resides in the service provider’s servers—OpenAI’s in the instance of ChatGPT. As a part of the provider’s databases, users have no control over the data they provide to the tool, which can cause great dangers, like sensitive data leakage.

How the service provider treats user data depends on each platform’s end-user license agreement (EULA). Different platforms have different EULAs, and the same platform typically has different ones for its free and premium services. Even the same service may change its terms and conditions as the tool develops. Many platforms have already changed their legal bindings over their short existence.

In-house tools: The second way is to build a private in-house tool, usually by directly deploying one of the LLMs on private servers or less commonly by building an LLM from scratch.

Within this structure, data resides in the organization’s private servers, whether they are on-premises or on the cloud. This means that the business can have far more control over the data processed by its generative AI tool.

Ensuring the security of off-the-shelf tools 

Ready-made tools exempt users from the high cost of technology and talent needed to develop their own or outsource the task to a third party. That is why many organizations have no alternative but to use what is on the market, like ChatGPT. The risks of using off-the-shelf generative AI tools can be mitigated by doing the following:

Review the EULAs. In this case, it is crucial to not engage with these tools haphazardly. First, organizations should survey the available options and consider the EULAs of the ones of interest, in addition to their cost and use cases. This includes keeping an eye on the EULAs even after adoption as they are subject to change.

Establish internal policies. When a tool is picked for adoption, businesses need to formulate their own policies on how and when their employees may use it. This includes what sort of tasks can be entrusted to AI and what information or data can be fed into the service provider’s algorithms.

As a rule of thumb, it is advisable not to throw sensitive data and information into others’ servers. Still, it is up to each organization to settle on what constitutes “sensitive data” and what level of risk it is willing to tolerate that can be weighed out by the benefits of the tool adoption.

Ensuring the security of in-house tools 

The big corporations that banned the use of third-party services ended up developing their internal generative AI tools instead and incorporated them into their operations. In addition to the significant security advantages, developing in-house tools allows for their fine-tuning and orienting to be domain and task-specific, not to mention gaining full control over their interface user experience.

Check the technical specifications. Developing in-house tools, however, does not absolve organizations from security obligations. Typically, internal tools are built on top of an LLM that is developed by a tech corporation, like Meta AI’s LLaMa, Google’s BERT, or Hugging Face’s BLOOM. Such major models, especially open-source ones, are developed with high-level security and privacy measures, but each has its limitations and strengths. 

Therefore, it would still be crucial to first review the adopted model’s technical guide and understand how it works, which would not only lead to better security but also a more accurate estimation of technical requirements.

Initiate a trial period. Even in the case of building the LLM from scratch, and in all cases of AI tool development, it is imperative to test the tool and enhance it both during and after development to ensure safe operation before being rolled out. This includes fortifying the tool against prompt injections, which can be used to manipulate the tool to perform damaging cyber-attacks that include leaking sensitive data even if they reside in internal servers.

Parting words: be wary of hype

While on the surface, the hype surrounding generative AI offers vast possibilities, lurking in the depths of its promise are significant security risks that must not be overlooked. In the case of using ready-made tools, rigorous policies should be formulated to ensure safe usage. And in the case of in-house tool deployment, safety measures must be incorporated into the process to prevent manipulation and misuse. In both cases, the promises of technology must not blind companies to the very real threat to their sensitive and private information.

Beyond remote work: insights and strategies for enhancing employee productivity and performance

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Remote work and the implications of continuing the process, including its potential impact on employee performance, are widely discussed. However, there is no right answer, and it is not one-size-fits-all. 

The future of work includes flexibility, employee experience, agility, and the responsible use of artificial intelligence (AI)—these significant shifts impact where and how employees work. With an increase in remote work options, we have seen positive trends in work-life balance, employee empowerment, inclusivity, and an increase in diverse talent. These factors are also known to increase employee productivity and retention. According to BCG, a considerable population of employees are ready to leave their jobs if they find their flexible work arrangements unsatisfactory. Based on their survey, approximately 90% of women, caregivers, individuals identifying as LGBTQ+, and those with disabilities, deem flexible work options as crucial in determining whether they will continue or resign from their current employment.

Remote work productivity is subject to debate due to various factors that must be considered. Some suggest remote work can increase productivity due to a flexible schedule, no commute, and fewer interruptions. While many employees thrive in a remote work environment, some find it challenging due to the discipline it demands.

Remote work was on the rise even before the COVID-19 pandemic. A July 2023 report from Stanford University found that working remotely has doubled every 15 years. Then, when the pandemic occurred, although devastating, it provided a new perspective for those previously constrained, forced to relocate, or live in less favorable locations to work for a specific company and advance their career. Worldwide ERC states that around 56 million Americans moved to new residences between December 2021 to February 2023 due to COVID-19-related shutdowns and the surge in remote work and online education. With such a huge increase in their number over the past few years, this begs the question: do employees working remotely demonstrate productivity?

Taking a deeper look into the study by Standord University, researchers shared that remote work employees’ productivity differs depending on perceptions—the nature of the research and the conditions under which it was conducted. The report revealed that workers believed productivity was higher at home (approximately 7% higher), while managers perceived it lower (around 3.5% lower). Another example, according to a poll by the video presentation applications mmhmm, 43% prefer office work and 42% favor working from home for peak productivity. Moreover, 51% of employees stated that working asynchronously or having the flexibility to set their schedules contributed positively to their productivity. Perceptions aside, the Stanford analysis found a 10% to 20% reduction in productivity across various studies.

The bottom line is today’s company culture is crucial. Ensuring work-life balance and putting the employees in the driver’s seat are the best ways to retain and increase productivity because they will feel valued and empowered. In a 2022 Microsoft employee engagement survey, 92% of employees say they believe the company values flexibility and allows them to work in a way that works best for them. An even higher percentage (93%) are confident in their ability to work together as a team, regardless of location. People have different preferences—some individuals opt for a hybrid approach, while others choose either remote or in-person work exclusively. 

Regardless of the work setup, company leaders and human resources (HR) or human capital management (HRM) executives should ensure that they can still make a lasting impact on employee performance. One measure involves establishing key performance indicators (KPIs) that assess innovation, program, project, and product success—the output, not the physical location. Another crucial step is developing a strategy that includes all future work options, such as in-person, hybrid, and remote choices. Employees tend to be more productive if there is a level of empowerment that allows them to decide where to do their best work.

Planning in person events makes a difference. Leaders who bring new hires and internal transfers, new to the team, on-site for several days should see an uptick in productivity post-gathering. In-person team or company-wide gatherings 1-4 times per year provide employees an opportunity to reset and socialize. Moreover, managers should bring teams together for major program and project kick-offs. When onsite in person, people being present makes a difference. Discourage using Teams or Zoom when employees are in the general vicinity. I have seen companies spew the importance of in-person just to fly employees into a specific location and have people take meetings from their desks or in a different on-site building-conference room, defeating the purpose of in-person interaction.

Having organizations foster all work options is critical and foregoes having to decide which is best. There is no right or wrong answer to this challenge; it should be considered a new way of working and requires future-forward ways of thinking, just as we do with emerging technologies. 


About the guest author:

Dr. Malika Viltz-Emerson is a Senior Global Human Resource Leader at Microsoft. She has over 20 years of experience in human capital management. Her mission is to identify and address the real-world challenges and opportunities for employees and the company, and design and implement optimal solutions that leverage the latest tools, technologies, and processes.

Research findings show gap in performance perspectives between leaders, non-leaders

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The Global Government Forum’s Responsive Government Survey shone a light on the different perspectives that leaders and other members of government organizations have about their performance. Compared to 2021, recent research found that public and civil servants have lost confidence in government responsiveness. Despite this, there is a high percentage of respondents—most notably belonging to those in leadership positions—who believe that their agency is more than capable of learning and responding rapidly. 

This positive outlook is present across the board among those in leadership roles, 73% of whom agreed that leaders were open to adopting new methods to better serve the public. This is in contrast to just 56% of managers and non-managers who agreed when asked the same question. Things are no different regarding morale, as 64% of leaders agree that it was high, in contrast to the overall response score of 54%.

Former cabinet secretary of Canada and current Jarislowsky chair of public sector management at the University of Ottawa Michael Wernick said, “It’s really important [for leaders] to develop [an] awareness of how their workforce is perceiving things—to take the pulse of their organization regularly and to deliver proof points to them.” Source: Global Government Forum

Stay ahead and empowered! Dive into the dynamic world of government strategy and performance management with the PERFORMANCE Magazine Issue 27, 2023 – Government edition. Download the magazine’s digital version at the TKI Marketplace and via Amazon for printed copies.

Measuring customer experience: 5 CX KPIs to keep an eye on

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Image source: grapestock from Getty Images | Canva

In modern business, focusing on customer experience (CX) is no longer a nice-to-have, but rather a necessity for businesses of all sizes. However, defining a successful customer experience can be difficult because many touch points form the customer journey. By using online surveys, companies can gain quantitative information about the customer experience to actively monitor trends that develop over time. Based on customer feedback, organizations can identify areas for improvement, adjust their strategies accordingly, set better goals for their key performance indicators (KPIs), and strive to deliver the seamless experiences that today’s consumers expect.

Customer experience KPIs

Research shows that CX is now competing with traditional factors such as price and quality in influencing customer loyalty and advocacy. According to  Forbes, 77% of consumers consider CX just as important as the main product or service itself.  PWC reported that even beloved brands risk losing 32% of their customers after one negative interaction. In addition, poor CX burdens the company with costs. To address this, this article outlines five critical CX KPIs that can be systematically monitored, evaluated, and optimized to help address customer service problems and strengthen a company’s connections with its customer base.

1. % Customer satisfaction score (CSAT)

This KPI measures how customers rate particular interactions with a company, such as getting a response from customer care or processing a return. Users can score their satisfaction with the experience on a scale from “very dissatisfied” to “very satisfied” by responding to an automated questionnaire sent to them. Monitoring the ratings depends on a company’s objectives, but the general rule is that anything above 85% is excellent, and anything below 60% requires rapid attention.

Calculation: CSAT = (Number of Positive Responses / Total Number of Responses) x 100

2. # Net promoter score (NPS)

The NPS, considered the most famous CX KPI, reflects the willingness of consumers to recommend a product to friends and acquaintances. To calculate NPS, a company can conduct a survey of customers from one query: “What is the probability that you will recommend the product to your friends?” The answer is given on a 10-point scale, where 0 is “I will not recommend it in any case” and 10 is “I will definitely recommend.” The respondents can be divided into three groups depending on the scores obtained: promoters, passives, and detractors. The majority of companies consider a score above 80 as excellent, a score between 50 and 80 as very good, and a score below 50 as good.

Calculation: NPS = % Promoters – % Detractors.

3. % Word of Mouth Index (WoMI)

An extension of the NPS index, the creation of the WoMI was motivated by criticism towards the traditional NPS. Researchers believed that the NPS made the incorrect assumption that if a customer does not recommend a product or service, then they are automatically considered detractors. This led researchers to make adjustments to the KPI in order to better reflect reality.  It tracks the recommendation, but from the opposite perspective: “What is the probability that you will discourage people from doing business with the company?” This can be rated on a scale of 0 to 10. Those who choose 9-10 on the scale of “dissuading” are categorized as “true detractors.” The threshold varies from one industry to another. It is better to have a lower score, as the target for most companies is less than 10%. To gain a comprehensive understanding of your company’s position among customers, we suggest employing both approaches to obtain a complete picture.

WoMI = (Number of Promoters – Number of Detractors) / Number of Respondents * 100.

4. Consumer Effort Score (CES)

The CES index, which was developed in 2010, is related to the idea that the more effort the product or service requires from customers, the less likely they are to stay with the company. As cited in an article, research by the Corporate Executive Board (CEB) shows that 94% of customers who have an effortless experience are likely to make repeat purchases. The KPI could be measured by the customer’s response to a statement like: “Thanks to the service/product of company X. I was able to easily cope with my problem.” with a rating scale of 1 to 7. Most companies typically receive CES scores ranging from 5 to 5.5. A score exceeding 6 is generally considered above average. 

CES = (Sum of response scores) ÷ (Number of responses)

5. Customer churn rate

Simply put, the churn rate is the number of users who stop any interaction with the company. Depending on the industry, this could mean that customers deleted their account, did not re-buy, or simply decided to switch to a competitor. In its simplest form, customer churn can be calculated by comparing the number of customers lost to the total number of customers. By dividing one metric by another, one can get the customer churn rate as a percentage of the total base. The most common acceptable churn rate is 5-7% annually.

Enabling effective CX measurement

KPIs must be monitored and measured in order to improve CX. To do so effectively, a system that accurately collects data from all channels should be considered. This allows requests to be categorized and common issues to be identified. In-depth interviews with both loyal and dissatisfied customers should be conducted to understand the root cause of any problems, as some of which could be related to support services. Consistency in tracking and improving CX KPIs is the key to ensuring decisions and actions in customer service adapt to changing customer sentiment and meeting their needs. 

Take your CX to the next level! Visit smartKPIs.com for a comprehensive, 360-degree view of CX KPIs.

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