Everyone wants to use the data. Big Data is in fashion, the Internet of Things has multiplied the opportunities to obtain statistics, the blockchain promises to guarantee the integrity of the data, and the achievements of companies that have already started using it are difficult to contest. However, there still seems to be a brake on use: we don’t quite trust the data our companies obtain.
This is demonstrated by a recent study by the consultancy KPMG in which they have interviewed almost 1,300 CEOs from countries such as the United Kingdom, Spain, the United States and Japan and belonging to a wide variety of sectors: automotive, banking, infrastructure, insurance, manufacturing, retail, etc.
From the outset, these CEOs are aware of the usefulness of data and its analysis. Those surveyed recognize that the use of numbers will be essential for the evolution of companies. To the point that 48% of them believe that there will be profound changes in their sector over the next three years due to technological innovation. But there is still a leap when it comes to moving from this recognition to the use and application of data, and not everyone dares to take it.
This is especially relevant in our world, that of logistics, where the integration of data throughout the supply chain is increasingly important and in which a multitude of numbers are produced in order to analyze its performance.
Why we don’t trust the data
The efficient use of data increases sales and profitability of companies. It allows them to get to know themselves, their clients, what they do well and what they do badly, what their clients stand out from them, etc. Ultimately, it gives them a framework of real numbers from which to make better decisions. Not trusting data analysis means turning your back on reality, in addition to investing money in obtaining and analyzing it and then not taking advantage of it.
The KPMG study shows some startling statistics that add to the problem of not trusting our own numbers:
Only 19% say they have no reservations about the validity of the data with which they have to make decisions.
36% say they can’t make data-driven decisions until they make significant investments in it.
45% consider that the depth of their knowledge regarding their clients is limited by the lack of quality of their figures.
Among the aspects that foster this distrust is the lack of familiarity with numbers. When the people who have to use them are suspicious of the algorithms that generate this data, and see it as something obscure, do not understand how they were obtained or do not handle the software used, the chances of these figures being left aside increase. Managers – and not just CEOs – must learn to trust the numbers and insights provided by their data analysis departments.
“Trust in data analysis should not be negotiable”
Have you ever been in a meeting where the question was asked: “And where does this number come from?” or a similar phrase? If so, it’s a good clue that there’s a lot of work to be done regarding the culture of number use in the company. As KPMG’s own report states: “Trust in data analytics should be non-negotiable.”
How to trust our data
KPMG proposes four areas for improvement to increase confidence in the data and its analysis.
The first of all is to be able to ensure that our data is reliable. Being able to be sure that when we account for a variable or a process we are obtaining the real data and that when we create an algorithm we are capable of taking into account all the variables it needs to be a reflection of reality.
Are you doing something with your data? Simply recording them, or even analyzing them without using the findings to make decisions, is a waste of time. What’s more, it will make the company’s personnel wonder why the numbers are collected and interpreted if they are not used later.
Data protection is a matter of global importance. Businesses need to ensure that the collection and use of data is done in accordance with the law and the privacy of their customers. Only once these bases have been secured can data analysis be made one of the pillars in business management.
Is your data analysis prepared for the medium and long term? Your strategy for its use should be designed for tomorrow and be easy to adapt to changes that may arise. Whether they are changes regarding the way of collecting the data or about the needs that our data have to respond to.
It is very common that when using data to make decisions, companies believe that they are much further from being able to do so than they really are. To complete this leap, it is essential to introduce the culture of numbers into the company. Explain why they should be a basic starting point for management and why leaving it out is competing at an inferiority.
It is also vital to carry out training programs. This will help workers to live naturally with the numbers and to be more reliable when entering data manually into the system (human error continues to be a very important factor in this type of failure and, therefore, in why do we doubt the data).
Another essential step is to clearly establish the criteria for our statistics. For example, in the case of logistics: what do we consider a correct shipment? According to the companies (or in the different delegations of the same company) the definition may vary. Some will equal it to delivery on time, others will add the fact that no claims are made, others will include that all the products in the order were available at the time they were requested, etc. Without clearly unifying these criteria, your figures will never be valid. An idea that also serves to integrate the various computer systems, which often represents another major obstacle.
Looking to the future, data analysis and Big Data do not stop gaining importance in companies. In many cases, logistics will be in the eye of the hurricane of this change and you will have problems if this process catches you on the wrong foot.
The more urgent the delivery service, the more expensive it will cost us to send a pallet. The two most common services for sending a pallet in Spain are the economic (48 hours) and the express (24 hours). Networks specialized in pallet distribution are constantly trying to reduce delivery times, as in the case of the a.m. of Palibex, with which we offer deliveries before 12 in the morning of the following day. Times that bring us closer to urgent parcel services.
Being proactive is one of the easiest ways to save costs on your shipments. More often than not, lack of foresight is among the reasons behind an urgent shipment. So pallets that could have gone cheap end up paying more than they should.
Fate, size, time, and weight are the first concepts that would come to mind for all of us, but the list doesn’t always end there. There is a wide variety of additional items that can add to how much it costs to ship a pallet. Do you need your pallet to be depalletized during delivery? Is it a delivery at street level, in a basement or do you have to go upstairs? Do you need a hatch or other additional means of unloading?
Another expense that usually catches many people off guard is taxes and customs procedures for shipments to the Canary Islands, Ceuta and Melilla. Although the recipient is often in charge of paying the taxes, it will always be better to clarify it with him before shipping, or we run the risk that the merchandise will be retained at customs and we will have one arranged between both parties.
There are even more concepts that may appear reflected on your invoice -such as gasoline, although it is more common to see it in international transport-, so a good rule of thumb is to consult your logistics operator for its possible existence.
Once you have these basic principles clear, it will be much easier for you to calculate how much it costs to send a pallet. As we mentioned at the beginning, by playing with weights and sizes you can start saving on your logistics, studying whether you can wait a little longer to gather more merchandise on your pallet, whether you can distribute the weight more appropriately according to your rates or how to assemble the merchandise on your pallets and up to what height.