It's important to remember that companies aren't deliberately trying to annoy us. When an online order ends up being out of stock, when an app goes offline and stays down for hours, when customer support replies arrive too late to help you, no one's happy about it. There are no mustaches being twirled in the boardroom.

It's just how modern systems tend to work. Products go out of stock before anyone realizes there's a problem. Services struggle for days before engineers can work out what went wrong. Even on a corporate level, research findings finally arrive after opportunities have already come and gone.

Companies don't slow things down to frustrate people. They slow down because, well, turning gigantic volumes of information into usable, reliable data takes time. Organizations are gathering more and more data from sensors, transactions, networks, and daily operations, for a valid reason: to be able to make better decisions. The problem is that in the real world, digesting so much data can slow things down. The gap between noticing that something needs to be changed and actually getting down to making that change is one of the reasons everyday life can feel less smooth than it should.

Any Alternatives?

NTT Service Innovation Laboratory Group's fast sparse modeling technology is an attempt to do something about that.

When computers analyze large sets of information, most of that information turns out not to affect the final analysis. Nevertheless, traditional systems still check everything, step by step, just in case. NTT’s fast sparse modeling allows computers to safely skip calculations that won't affect the result, while still making sure the final answer is exactly the same as if every step had been checked. Sparse means the system assumes that, in any large pile of data, only a small part actually matters. Fast sparse refers to how it learns which parts matter early on, then skips the rest, thereby reaching the same answer much more quickly.

Faster analysis is only useful if people can trust it. According to NTT’s research, the new algorithms can speed up analysis by as much as seventy times without changing accuracy. In practical terms, work that once took weeks can be completed in a day, sometimes even less. This holds true across different types of data, including simple tables, grouped information, network data, and hierarchical structures.

Calculating Only What Needs To Be Calculated

The quicker data analysis comes from avoiding work that would never change the answer. In large analyses, most variables, time points, or signals end up having no effect on the result, yet traditional systems still process them fully. NTT’s algorithm identifies these non-contributing elements early and removes them from the calculation, cutting out large amounts of wasted computation without altering the outcome.

So we can look forward to companies getting better at coping with all their data. Here are some examples of how that could be seen.

Already In Use

Some of the fast sparse algorithms have already been integrated into Node-AI, a commercial no-code AI tool provided by NTT DOCOMO BUSINESS that allows the technology to be used in real business settings, without requiring specialist data science skills. The same technology is also being used internally by NTT for preparing affiliate marketing data for analysis.

Until now, organizations have had to wait for data analysis to fully run, be checked, and be trusted before acting on it. Acting before that was completed meant relying on partial results, which brought a risk of making the wrong call. By making large-scale analysis both fast and reliable, NTT's fast sparse modeling technology could potentially shorten that delay, so that problems could be sorted out earlier, when fixes are smaller and easier to manage.

Everyone's A Winner!

For most of us, we won't realise this is even happening. It won't become a named feature or visible product and will only show up indirectly. Services will feel more reliable, supply chains will recover faster, and decisions will seem to be better timed. It's not going to be something that causes huge excitement; but we will perhaps notice there are fewer disruptions or moments when the solution arrives too late to be needed. Going from reacting too late to responding in time is where the value will lie.

Innovating a Sustainable Future for People and Planet

For further information, please see this link:
https://group.ntt/en/newsrelease/2025/09/08/250908a.html

If you have any questions on the content of this article, please contact:
Public Relations
NTT Service Innovation Laboratory Group
https://tools.group.ntt/en/news/contact/index.php

Daniel O'Connor

Daniel O'Connor joined the NTT Group in 1999 when he began work as the Public Relations Manager of NTT Europe. While in London, he liaised with the local press, created the company's intranet site, wrote technical copy for industry magazines and managed exhibition stands from initial design to finished displays.

Later seconded to the headquarters of NTT Communications in Tokyo, he contributed to the company's first-ever winning of global telecoms awards and the digitalisation of internal company information exchange.

Since 2015 Daniel has created content for the Group's Global Leadership Institute, the One NTT Network and is currently working with NTT R&D teams to grow public understanding of the cutting-edge research undertaken by the NTT Group.