Carlo and Paola have been living together for several years; they seem a perfect couple. No one knows that their union is soon destined to end, not even them. Yet within their “family organization” all the elements indicating unequivocally that they are heading in that direction, can already be seen. It is, for example, the use of a credit card in a restaurant for an amount that is not compatible with someone dining alone. Or the location information contained in the “exit” data of a photo on a smartphone, information indicating a position a little too far away from the place where one of the two should have been on that occasion. Then there is an SMS identifying an unexpected bank transaction, of which one of them is unaware and the other is concerned to get rid of as soon as possible, without taking into account that all movements are visible on internet banking in real time.
Any organization, be it family, public or business, cannot ignore the fact that at every moment huge volumes of information are being generated. This cannot be ignored, on the contrary in fact it needs to be managed better in order to benefit the organization itself in relation to its context.
To promote industrial success, or the best service for citizens, it is therefore necessary to understand this phenomenon, to learn to better manage the available information and thereby enhance the data culture.
This is an approach that puts young and agile companies at an advantage, especially those connected to new technologies, in that they are more used to dealing with business that is often related to data, metrics, indicators and information in general.
In contrast, older companies usually consider data as an operational tool to drive the business daily and very rarely manage to use it as a strategic tool to guide production choices for the future or to properly direct innovative processes.
This difference in approach is by no means negligible, in fact, as indicated by among others, the Fostering a data-driven culture report from the Economist, companies that have a deep-rooted and developed data culture often demonstrate significantly better financial performance than their competitors who are not able to handle data as efficiently.
This result depends on the fact that the data, when used appropriately, is a powerful enabler that allows informed decisions to be made, based on reliable information, avoiding as much as possible the emotion-driven choices that are not supported by numbers and indicators.
It is therefore important that the data is available and that the organization is able to take best advantage of it in order to achieve its financial and industrial targets.
One wonders then what are the guidelines that will enhance the data culture within organizations, let’s have a look at some.
Measure and memorize everything
Whatever our organization may be, it is important to collect data in the most granular way possible and ensure it is equipped in-context relationships. This is very easy to do with financial data, as every company should have accurate accounting. The task becomes a bit more complex if we turn to marketing data; we should be able to understand which are the most exciting target audiences and what is our brand sentiment. It becomes even more complex when we start to want to collect data arising from production: how many pieces produced by individual machines, how much waste, which and how many lines between different stages of production and so on. We need to equip our systems with sensors capable of collecting all this data and storing it. Yes, but where and how do we store it?
Single aggregation point
Having a lot of data stored on different databases that are not able to talk to each other has the side effect of making the correlation between the information very difficult. Knowing that there was an increase in orders, and as a result, of production, without knowing that this increase is the effect of a specific marketing campaign and increased product quality, is totally useless. The data must be placed in relation to each other even if they belong to different domains that are seemingly unrelated to each other.
Openness, transparency and sharing
The data belongs to the organization and as such represents an important asset, whether atomic or structured, detailed or aggregated. Making it available throughout the organization, safeguarding the confidentiality of certain information in relation to the organizational context, can contribute to new ideas thanks to the different perspective with which the data is viewed, understood and interpreted. It is not rare in fact that some correlations between data and thus between certain phenomena, are perceived by people who deal with something completely different within the organization. To further enable this phenomenon incentive-based logics can be inserted on the innovative use of the data.
Ease of access and use
If we want a tool to be used, it must be easy, fast, intuitive and possibly interesting. Providing employees with a spreadsheet containing hundreds of columns, or read-only access to an SQL database is totally pointless and will produce only one result: nobody will use it. If we want the data to have real value and therefore be utilized to its best, we must provide employees with analytical tools that are able to access data in an easy and interesting way.
Take decisions solely on the basis of the data
After collecting the data, placing it in relation with other data, storing it, creating correlations, making it transparent, open and accessible to everyone, the time comes to use it to its best as a tool to define strategic choices and identify new innovation pathways. It is therefore important to establish that every decision, at all levels, should be taken solely on the basis of available data, avoiding intuitive decisions as much as possible.
Growth towards a true data culture is a long process, which requires the involvement of the entire organization and can have a major impact both on the technology used and on organizational choices. For this reason, it is appropriate to involve all levels of the organization and make sure that decision-making is based on the data available.
Moreover, without data to support a decision, it is just people acting on an opinion.