Can Artificial Intelligence (AI) Improve My Business and Consumer Apps?
It is impossible to listen to the news, read a business publication or browse social media without finding an article or story about Artificial Intelligence (AI).
Author: Kartik Patel
Can Generative AI (GenAI) Help My Business?
Whether you are in the business of technology, or an average citizen, there is no doubt you know about Artificial Intelligence (AI) and you have probably heard or read about the advances made in Generative AI (GenAI).
According to Gartner business surveys, GenAI has become one of the most adopted and deployed technologies, and it is either in use in many industries and businesses, or it is in the works.
As a senior manager in a software business, or a corporate CIO, a software engineer or a consumer, you are probably thinking about how you can use GenAI to make your product better, or your life simpler. If you ARE in the business of technology, you may already have started a GenAI project.
But, it may be wise to exercise some caution. You know the old adage, ‘just because you can, doesn’t mean you should?’ That certainly applies to GenAI.
Yes, this technology has advanced enough to offer some value in some instances, but it should not be widely adopted without understanding its current limitations. Don’t let the promise of GenAI blind you to the fact that it is not yet a mature technology and that it is not suitable for all applications.
Before you start your project, you should consider the following factors:
- GenAI alone is not the magic potion many think it is. In fact, the best use of GenAI is as a component of a holistic landscape of technologies, which may or may not include other types of artificial intelligence (AI) techniques.
- Business use cases are a wise addition to your strategic discussion. How and where will your business use GenAI and does the addition of this technology add value or provide competitive, productivity or collaborative improvements? Implementing GenAI just because it is cutting edge, does not add value to your organization.
- The cost of implementing these new technologies must be considered. That consideration should include the estimated useful life of the investment and its return to the organization.
- For some tasks like content summarization for presentations or reports, or routine content creation, standard product descriptions, etc., GenAI may be a welcome addition, and will provide productivity improvement for your team.
- When considering the use of GenAI, it is important to understand how and when your team will use the capabilities and set reasonable expectations for its use. If and when you decide to implement GenAI, it is equally important to train and inform your team and help them understand what they can achieve with this technology. You must also ensure that the team understands what GenAI will NOT do for them. There is a lot of hype out there, and team members may think that GenAI is going to either a) replace their position, or b) give them back 50% of their time for other tasks. It is likely that neither of those scenarios will be true, so be sure your team understands the transition, what they can expect, and what you will expect of them.
- Involving experienced team members in the AI process is imperative. You can’t ‘set and forget’ your tasks without risking incorrect output or issues that will affect customer satisfaction or put your business at risk. Consider how and when you will monitor and manage output and what human intervention is required for the use you have imagined in your use cases.
- While we are on the subject of expectations, let’s remember that, while the future of GenAI is promising, the current state technology is not a boiler plate. It is not a one-size-fits-all solution that can be hurriedly put into place, nor will it solve all your problems.
There has been much marketing hype about GenAI, but at the end of the day, if your business is going to invest time and money in this technology, it must establish a reasonable strategic initiative with measurable metrics and risk assessment and management reviews.
Before your business tackles a GenAI investment project, and all the technology, cultural and management changes that it requires, ask yourself a) what problems does my business have and what are our most important priorities, b) Can GenAI realistically help our business solve or reduce these problems and c) how can I measure and manage this new approach to prove my theories?
As we have outlined in this article, it is important to recognize the limitations of the current Generative AI (GenAI) solutions, and develop a thorough and complete understanding of your prospective business use before making a decision to invest in and implement this type of solution in your organization. Contact Us to find out how we can help you plan and achieve your goals. Artificial Intelligence (AI) in Analytics, Artificial Intelligence Development, White Paper: What is AI and How Can It Help My Business? Explore our articles on AI: Generative AI, the Benefits and Applications, Ideas to Get You Started with Generative AI, Understand AI, OpenAI and Chat GPT.
Original Post : Generative AI (GenAI) Is NOT a One-Size-Fits-All Solution!
When an enterprise undertakes an Augmented Analytics project, it is typically doing so because it wishes to initiate data democratization, improve data literacy among its team members and create Citizen Data Scientists. The organization looks for a solution that is easy enough for its business users and intuitive enough to produce clear results; one that also provides sophisticated functionality and features and will produce a suitable Return on Investment (ROI) and Total Cost of Ownership (TCO).
Nothing…and I DO mean NOTHING…is more prominent in technology buzz today than Artificial Intelligence (AI). The use of Generative AI, LLM and products such as ChatGPT capabilities has been applied to all kinds of industries, from publishing and research to targeted marketing and healthcare. Gartner recently estimated that the market for AI software will be nearly $134.8 billion, with the market growing by 31.1% in next several years. In a recent survey of C-suite executives, 80% of said they believe AI will transform their organizations, and 64% said it is the most transformational technology in a generation.
You have decided that your business can benefit from an analytics solution. Now, it is time to convince your executive team, your managers and your users. If you are to gain approval for your initiative, you must take the right approach.
In this article, we discuss some of the primary factors you must consider to build and present your initiative to the various audiences within your organization.
A four-year study of businesses implementing analytics solutions found the following:
- Less than 50% of the businesses reported measurable results
- Only one third of the businesses met their objectives for user adoption
- 77% said that user adoption was a challenge
- Only 20% reported that analytics insights provided positive business outcomes
Before you give up on your initiative, consider this: most software projects fail because of poor planning and execution. So, if you can plan appropriately, you will be way ahead of the game. Here are a few factors you will need to include in your review and planning process.
IT Team – Be sure you include your IT team in your planning. You will need a comprehensive understanding of your existing technology, hardware, network and devices and you will need the help of your IT team to assist you in planning roll-out, estimating the cost of new technology to implement your plan, and interviewing prospective solution vendors and service providers.
To Gain Their Buy-In: Involve them, and ask for their opinion. Build a plan and allow them to review it and comment. Listen to their concerns. Ask for their support in working with users. Ensure that the vendor you engage will provide support for IT so that your IT team is not overwhelmed with new and expanded tasks and responsibilities.
Executives – Senior executives will be looking at investment costs, return on investment (ROI) and the total cost of ownership (TCO) and at the value you claim this solution will provide. Be prepared before you approach your executive team. Be sure you have involved all the right players and include representatives of these groups to address concerns and answer questions if the executive team wants to probe and challenge.
To Gain Their Buy-In: Be prepared! Keep your presentation at a high level, but be sure you have the details to answer their questions if and when they arise. Provide more detailed reports for them to peruse at their leisure. They probably won’t dive in, but they will be reassured that you have done your homework. Focus your presentation on a) reduction of cost, b) competitive positioning with EXAMPLES of how analytics will help achieve these goals, c) doing less with more and making the company more productive.
Managers – Managers will be concerned about putting more strain on business users and team members and, since the modern approach to business intelligence and analytics involves the business users and their transition to Citizen Data Scientists, you must focus on the managers and what’s in it for them. How does this help them to do their job? They are accountable for results, and they only have so many team members to get the job done. They are also evaluated, based on how their employees see their management style and effectiveness, and they will not want their team to complain.
To Gain Their Buy-In: Focus on their business processes and workflow and how augmented analytics and business user involvement can speed the process, ensure more fact-based decisions and make the managers look good, without putting more strain on the business user. Ensure that your vendor and IT team have a plan to reassure the managers so that they don’t worry about the use of sophisticated systems that will take a lot of training time. How will the roll-out be done? You want a controlled approach so that users are not spending a lot of time getting up to speed and neglecting day-to-day tasks.
Business Users – As usual, the buck stops with the team member. They are the ones who will be asked to change their processes, learn new systems and take on new responsibilities. Look again at the survey results reported above and notice how poor user adoption affected analytics projects. If you can’t get your users to adopt the solution, your project will fail. Your executives, IT team and managers may think this is a great idea, but they will blame you if the team does not respond positively. Involve users in advance to gather and thereby anticipate their concerns when you present your findings and your plan. Do not be defensive. Listen to their issues and incorporate those concerns into your review and selection of a vendor and a solution. With the right self-serve augmented analytics solution and service provider, you can assure them that a) the system will be easy to use and won’t take a lot of time to learn, b) will make their job easier and c) will give them a career advantage.
To Gain Their Buy-In: Listen, digest and address concerns. Understand that there is a culture shift involved in this process and be sure you acknowledge that at all levels of your presentation, including your executive team. Let’s not pretend this new idea will not require change. It will. But if you work with all levels to assure that new responsibilities will be rewarded in employee evaluations and that the team will be supported by managers who are true champions of the process, you will be ahead of the game. Try to meet with users without IT and managers in the room, and then regroup with the appropriate staff (managers, IT etc.) after you have had a chance to evaluate and address user concerns. Users are more likely to be receptive if they aren’t put on the spot. BUT be sure to control the discussion and the environment so it doesn’t turn into a complaint session. When you are ready to do your sales pitch and you have addressed all their concerns, focus on the user and their hot buttons. Tell them how this solution will help them and assure them that the vendor and your implementation team will be there every step of the way. And then follow through!
For more information and details on how to plan for and achieve success with an augmented analytics solutions, read our free articles: ‘A Roadmap to ROI and User Adoption of Augmented Analytics and BI Tools,’ ‘Making the Case for Embedded BI and Analytics,’ and ‘Integrate Augmented Analytics and Digital Transformation to Achieve Continuous Business Improvement.’
In this article, we have included just a few of the considerations and factors you will have to address in order to build a plan for your Augmented Analytics project. It is a good idea to engage an IT expert – one with the skills and experience to anticipate your concerns, work with you on industry and business issues and plan for a small, medium or large enterprise installation. An expert team can help you manage the technology review and requirements, and plan for your presentation, etc. Be sure you choose a vendor with sophisticated augmented analytics features and functionality in an easy-to-use environment that will support the transition of your business users to Citizen Data Scientists and ensure that your project will succeed. Contact Us to find out how we can help you plan and achieve your goals. It really IS possible!
Original Post : How Can Assure Approval of My Analytics Project?
In recent studies, 49% of the organizations surveyed about Digital Transformation (Dx) initiatives reported that Dx gave the business the ability to better manage business performance through data availability. When it comes to Digital Transformation strategies, the wise enterprise knows to involve its team members in the requirements planning and in planning for execution and transition.
In assessing the enterprise landscape and planning for a Digital Transformation (Dx) transition project, every organization will certainly focus on technology and infrastructure. Technology is, after all, inherent in the very nature of a Dx discussion. Infuture Institute recently published a study that describes the critical factors in a Digital Transformation (Dx), and one of the most provocative insights states that, ‘What we need is…the change of attitude in the approach to digital transformation – from a technological approach to the humanistic approach (human over technology, not technology over human), i.e., focus on the employees within the organization and the needs and expectations of customers and consumers.’
When businesses consider implementing a Digital Transformation (Dx) strategy, many will struggle with the idea of improved customer satisfaction. How can streamlining and automating processes and enabling the use of technology translate into improved customer interaction and build brand and relationship stability?
There has been a lot of press about the concept of Data Democratization and the resulting improvement in data literacy across the enterprise and yet, many businesses still see this democratization effort as restricted to middle managers or to the use of analytics within the four walls of the headquarters or regional offices of the enterprise.
But, as with any other discussion of ‘democracy’, there is no true benefit to this concept unless data is truly democratized across the business landscape. The real focus on data democratization is meant to reach the front line workers so that every team member has access to simple, easy-to-use analytics and can use data in a way that is meaningful to their job. It isn’t enough to ask a team member to use data in reports. If the business user and team member does not see or feel the value in their everyday tasks, the business has failed at data democratization.
If you are willing to acknowledge that the real operational decisions are – and must be – made on the front lines, then it is wise to give your team the tools they need to make those decisions in a more efficient, effective manner.
The first step is making the data available to every user. That means planning for and rolling out analytics across the board, typically by starting with one business unit or area and then rolling the initiative out from there until the entire enterprise has access to appropriate, timely, integrated data for use in analytics and decision-making.
If you are managing a financial institution, that would mean giving access to these tools to your loan officers and your customer service representatives. If you are in sales, your sales reps need to be able to see data and metrics for products, conversion of prospects to customers, returning customers, bundled product and sales initiatives, upcoming discounts and promotions, and more. If you are working in manufacturing, your production line employees need to see and anticipate scheduled maintenance and identify issues with equipment performance, downtime, etc.
Give your line workers, customer-facing representatives and team members access to augmented analytics that are easy to use and will not frustrate them as they attempt to solve problems and identify opportunities to improve or create new ideas to improve results. Predictive analytics can help users define the risk inherent in approving a loan for a particular client or it can help sales reps to establish a reasonable target and not overestimate sales for a particular season or location.
The team members on the front lines are the ones that have to make the tough decisions and, while they have targets and goals and marching orders, the use of analytics to make day-to-day decisions will help everyone by establishing a baseline and measuring whether certain tasks or activities are supporting those goals. It will also help your team by making them more accountable and empowering them with the tools they need to make a confident decision. There is no time for guesswork or opinion in today’s competitive, rapid paced environment.
If you are willing to acknowledge that the real operational decisions are – and must be – made on the front lines, then it is wise to give your team the tools they need to make those decisions in a more efficient, effective manner.
Giving a Sales Manager an analytical tool allows them to monitor and measure performance by location, region, sales representative, product, and other factors. Giving a Sales Representative an analytical tool allows them to make a difference, to see what is working in real time and to share, collaborate and make decisions that will truly affect the bottom line. It isn’t enough to report on the history. Give them the right tools and democratize your data for front line workers and you will help them MAKE history.
Consider the logic of a store manager keeping the key to the stock room on a key chain. If workers have to find the store manager every time they need something out of the stock room, there is a loss of productivity and empowerment. If a stock room has a lock that is opened by swiping an employee ID card, the employee gets what they need, the customer is served and the business has the data it needs to govern and manage its stock safely.
Data is a tool. Data is a part of your product and service offering. That data should drive your decisions on pricing, changes in workflow and activities, planning and forecasting and resource and equipment management. When you put data analytical tools in the hands of your front line workers, you improve the agility, flexibility and performance of your business.
Original Post : Data Democratization On the Business Front Line!
This article should serve as a plea on behalf of the average business user!
Business users are business professionals who have expertise in an industry or market arena or perform a function to support the ongoing operation of the business – professionals who may be front line workers on a production line, finance professionals, sales representatives, non-profit office workers, medical researchers, middle managers, regional managers for retail chains, transportation dispatchers or…well, you get the idea. These team members know their job and they do it well. But, they probably don’t have the technical skills to write a SQL query, or to filter out the columns and fields for an analytical search in order to get the results they need to make a decision.
