Generative AI increases productivity and product quality.
And the less skilled the worker, the more so. The Nielsen Norman Group study clears up any doubts about this and solves the question of what kind of companies this technology is for. Do you want the answer now? Spoiler Alert: It’s for all companies.
Generative AI increases productivity and product quality. And the less skilled the worker, the more so. The Nielsen Norman Group study clears up any doubts about this and solves the question of what kind of companies this technology is for. Do you want the answer now? Spoiler Alert: It’s for all companies.
All managers spend a lot of free time thinking about how to improve the business: first you must know it, and to know it, you must measure it: measure the time of a process, the time it takes to get paid, the cost of delivering one box versus delivering several… and so on up to hundreds of measurements.
Any management tool worth its salt incorporates hundreds of ratios that are the result of measurements, and companies are measuring more and more. It is essential to measure in order to know the situation and set objectives and strategies to achieve them. Who has not heard of KPIs (management indicators)?
Measuring has long since ceased to be an obstacle. We have data on everything. But at this point, what do we do with this data, and are we making the most of it? Based on what I see around me and sadly, the answer is a resounding no.
The challenge now is to interpret the data in such a way that we can draw conclusions that will help us achieve our objectives. But most organizations lack a professional team capable of interpreting and planning actions that lead to improvement.
It is often frustrating to ask a team trained to do business “as usual” to interpret data to improve their work. This is because a worker becomes particularly good at something by repeating the task rather than by having a critical spirit aimed at constantly improving it. How close to home is the saying “the devil knows best when he is old”.
And if a small or medium-sized organization does not have the human resources to take advantage of data, the long-term problem is that companies with fewer resources will lose competitiveness faster and faster to those that can hire professionals who are willing to pay them for the job if this benefits the organization as a whole. Indeed, these are employees who are more expensive to hire, but whose passage through an organization leaves a trace of cost reduction and service or product improvement.
But generative AI has arrived to provide a new opportunity for companies that do not have access to those “1st division” professionals. The Nielsen Norman Group (NN/g) study (nngroup.com/articles/ai-tools-productivity-gains) reveals the impact of AI from productivity and service excellence approaches. In the conclusions derived from a total of 3 studies in very different positions, an increase in productivity of up to 126% has been obtained, and in all cases an improvement in the quality of the product or service.
Unlike other disruptive inventions that humankind has experienced throughout history, generative AI is deployable in any organization and, guess what, it produces effects almost immediately. In two of the 3 studies conducted by NN/g, they measured the outcome after only one use of the AI tool. And the results speak for themselves: a 59% and 126% increase in productivity, respectively.
Nubeprint implemented its ML (machine learning) engine in 2017, thanks to which the distributor with cost-per-copy contracts or subscriptions has been able to reduce its stock, improve deliveries, reduce incidents, improve its costs, and also gain productivity while increasing customer satisfaction.
