In an ever-evolving business landscape, aligning technology choices with mission statements is crucial to resilience and success. Measuring the impact of AI and taking an inside-out approach further drives digital innovation.
The Internet is full of articles, videos, podcasts, and other resources about AI and its many uses. With all this information about the benefits of AI, business leaders may feel like they are not doing enough with this transformational technology.
As a result, companies may be tempted to adopt AI tools because they are new, impressive to customers and other stakeholders, or because their competitors use them. However, investing in AI for these reasons does not represent a path to success.
To grow, improve, lead and innovate, companies must choose AI tools that align with their needs. Successful companies understand their core operations and use technology to support their goals. Below is an example of how companies can connect their AI digital innovation with their key business drivers.
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Set goals clearly
A company's objectives must derive from its mission. Let's assume it's to help women in corporate roles succeed by taking the burden of shopping off their to-do lists. In this case, one objective might be to provide highly efficient personalized shopping services.
It is advisable that goals follow the SMART Framework , which means they should be specific, measurable, achievable, relevant and urgent. If necessary, break goals down into smaller objectives to meet these criteria. For example, expanding into new markets is crucial to align with the example company's mission of helping busy women succeed. A SMART goal in this context could be to acquire 100,000 new customers in Colorado within a year.
With this objective clearly defined, a company can consider which AI developments and solutions can support it. Predictive analytics could analyze data related to the purchasing habits of women in corporate jobs, along with where they spend time online. This information would help the company decide where to advertise its services.
Predictive analytics use cases
Greater efficiency can be supported with chatbots . When women access the service for the first time, a chatbot can guide them through the sign-up process, provide information about all available services, and help them place their first order. Later, chatbots can help with simple customer service questions and find a human representative to resolve more complex issues.
Providing suggestions on items to buy can be supported with personalized recommendations. A good example of this type of service is Amazon's “Inspired by your recent purchases” and “Related to items you viewed” sections. The example company could implement similar sections on its website so that women can get useful insights based on their browsing and purchasing histories.
This way, digital innovation efforts can be mapped to the company's objectives, ensuring that technological advances directly contribute to achieving them. This planning prevents companies from spending on solutions that, ultimately, will not improve their financial results.
Consider customers
Companies that use AI must also map their use according to customer needs and preferences. Doing so requires robust methods for understanding these needs and preferences, including the following strategies:
Feedback opportunities: Businesses can request feedback from customers at various points in the customer journey. It could be about website navigation, feedback about their online shopping experience, looking for ratings on the items they buy, or the customer service process.
Consumer behavior: Companies must analyze what customers communicate based on their behavior. Buyers who make repeat purchases are likely to communicate that they are satisfied with the company, its processes and products. Customers who make a purchase, return items, and do not make additional purchases are likely communicating that they are dissatisfied with one or more aspects of the company.
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Surveys: One of the best ways to find out what customers think of a company is to ask them directly. Surveys provide good information about a company's performance in specific areas.
AI can compile information from all of these sources to help companies determine where to add or remove other AI solutions to help customers get more of what they want and less of what they don't want. This type of strategy can ultimately drive customer loyalty and revenue growth.
Involve employees
Companies benefit from employee insights for customer-focused improvements and operational efficiency, which is crucial to customer satisfaction and ROI. Encouraging employee input on the use of AI is critical.
Company leaders, upon hearing this information, can consider which AI solutions can solve specific problems. For example, a transportation management system could better anticipate delivery problems and assign more realistic delivery dates. A company could use this process to improve customer satisfaction. But you could also go further and make on-time gift delivery part of your marketing messages.
Use cross-functional collaboration
Communication problems between departments within companies are an old problem in the corporate world. One solution could be an AI-based Customer Relationship Management System (CRM) within an organization. By collecting specific information about sales calls, this system can help the marketing department understand pain points and tailor their messages to address those points.
Analyze AI trends
Organizations should regularly analyze market trends and emerging technologies to identify opportunities for digital innovation. The following sources of information may be helpful in learning about AI trends:
Competitor analysis: Studying how competitors are using AI technologies can help companies identify potential gaps in their own AI development.
Networking and industry events: Attend AI-related industry conferences, webinars, and networking events. They provide opportunities to hear from AI experts, connect with peers who can offer advice, and gain valuable insights into AI trends.
Internal data analysis: This is the primary source for leaders to assess the impact of AI on operations and performance by uncovering project outcomes, costs, efficiency and customer satisfaction. Offers insights into the benefits of AI and areas for potential investment.
Measure success
Another way to ensure AI-based technology implementations are ingrained in business drivers is to measure the success of those already in use. The following methods can be used:
- Key Performance Indicators: A useful KPI in relation to an AI-based CRM could be “30% increase in leads”. KPIs can be related to revenue growth, cost reduction, customer satisfaction or operational efficiency.
- ROI: Companies can calculate the ROI of an AI implementation by comparing implementation and maintenance costs with the financial benefits achieved.
- Customer feedback: Customer reactions can be in the form of surveys, feedback forms, or user interviews. These sources offer insights into user satisfaction, usability issues, and potential areas for improvement.
- Time and Resource Savings: Businesses can evaluate the time and resources saved through AI Automation .
- Adoption and integration: Companies can gather this information from usage metrics, user surveys and feedback, user support requests, workflow efficiency, and comparison to industry benchmarks.
Information from all of these sources can be used to understand what types of AI-based technologies are useful and to what degree. From these findings, business leaders have more information to make decisions about future investments in AI.
An inside-out approach
In today's dynamic business environment, companies understand the importance of internal resilience. This involves flexible systems and processes that can withstand challenges, starting with a clear mission and vision. The video highlights resilience and how digital solutions, including AI, drive business success.
In conclusion, aligning business and technology choices with mission statements promotes long-term flexibility and goal congruence. This strategic alignment helps companies avoid costly deviations and achieve important objectives such as improving customer experience, operational efficiency and profitability. Successful companies prioritize an inside-out approach to digital innovation, enabling them to confidently navigate uncertainty and pave the way for lasting success.
