Supply chains moved quite early on towards computer-based management systems. Yet, as a result, many large companies have decade-old supply chain systems which tend to be sluggish when it comes to crunching a lot of data. Certainly, tons of Big Data technologies are available nowadays, but companies are treading carefully. Many, if not most, of those Big Data companies are critically dependent on top-notch engineering talent to get their technologies working smoothly; and not all companies succeed, unlike Facebook, in rewriting layers of Big Data technologies for making them work.
Being able to process vast amounts of data has been a long-standing commitment of Lokad. Indeed, optimizing a whole supply chain typically requires hundreds of incremental adjustments. As hypotheses get refined, it’s typically the entire chain of calculations that needs to be re-executed. Getting results that encompass the whole supply chain network in minutes rather than hours lets you complete a project in a few weeks while it would have dragged on for a year otherwise.
And this is why we started our migration towards cloud computing back in 2009. However, merely running on top of a cloud computing platform does not guarantee that vast amount of data can be processed swiftly. Worse still, while using many machines offers the possibility to process more data, it also tends to make data processing slower, not faster. In fact, delays tend to take place when data is moved around from one machine to the next, and also when machines need to coordinate their work.
As a result, merely throwing more machines at a data processing problem does not reduce any further the data processing time. The algorithms need to be made smarter, and every single machine should be able to do more with no more computing resources.
A few weeks ago, we have released a new high-performance column storage format code-named Ionic thatis heavily optimized for high-speed concurrent data processing. This format is also geared towards supply chain optimization as it natively supports the handling of storage distributions of probabilities. And these distributions are critical in order to be able to take advantage of probabilistic forecasts. Ionic is not intended to be used as an exchange format between Lokad and its clients. For data exchange, using flat text file format, such as CSV, is just fine. The Ionic format is intended to be used as internal data format to speed-up everything that happens within Lokad. Thanks to Ionic, Lokad can now process hundreds of gigabytes worth of input data with relative ease.
In particular, the columnar aspect of the Ionic format ensures that columns can be loaded and processed separately. When addressing supply chain problems, we are routinely facing ERP extractions where tables have over 100 columns, and up to 500 columns for the worst offenders. Ionic delivers a massive performance boost when it comes to dealing with that many columns.
From Lokad’s perspective, we are increasingly perceiving data processing capabilities as a critical success factor in the implementation of supply chain optimization projects. Longer processing time means that less gets done every single day, which is problematic since ultimately every company operates under tight deadlines.
The Ionic storage format is one more step into our Big Data journey.