Managing the big picturePublished on 09 Jul, 2018
Managing the big picture
In the business world you have to be aware of what happens around you. Especially, you have to be aware of what happens inside your own business. The more information you have around your fingertips the better. Even the smallest details and expenses should be stored somewhere in some form. You also should make use of that information efficiently. If you just collect information to dust to your bookkeeping its potential is wasted. Making connections between collected data is the key to management and improvement. The big picture is a difficult subject and usually only a select few inside a company can comprehend it. There are a few things that are necessary if you want to keep your big picture in line: platform, integration, data channels, data model and analyzation.
Platform is the interface that everything is built on. Surprisingly, only a few corporations have actually implemented a platform that covers corporations’ every aspect. They might have a certain platform to cover e.g. accounting or social media communication but rarely everything is gathered under the same roof. This might work to some extent but when everything is connected, platforms’ true potential is realized. Imagine a single portal where you can access information from marketing materials to premises energy consumption. When people can see what happens around them, even if it’s outside their own area of expertise, they start to see the big picture too and that leads to unimaginable innovations and ideas.
Integration is closely related to platform. Platform is only an empty shell if nothing is inserted in it. Generally integration means bringing everything to a one single place. Platforms’ job is to work as a ‘clickable’ bridge between integrated entities, integration is what tells where the bridges should lead to. For example imagine yourself a platform and to that platform you would like to bring marketing materials, supply stock, employees currently working, premises space usage, rooms’ temperature and air quality information, etc. That is called integration.
Now what are these bridges between integrated entities and the platform? These are data channels. Data channels, aka. Data busses, might sound like a simple thing at first, something like “you just copy stuff and you paste it to somewhere else”. Very rarely that’s the case. In order to move data it first has to be transformed into a different type of data and from that back to the initial type or even a third type of data. These can be achieved with e.g. API interfaces which can grant requests for or pass ‘stuff’ along. These are the small mailmen that enable communication between integrated solutions.
Data model is what manages the communication flow of the data channels. Mailmen need some sort of a post office, right? Data models tell data channels where they should move and when they should start moving the information. Sometimes there needs to be multiple smaller data models under a single platform. When there are multiple integrated entities, every single one adds more challenge to needed data management. Sometimes the smaller data models have to talk to each other in order to get the message across to the big data model. When the platform grows, the data models’ workload increases accordingly.If you have managed to get this far in your big picture management development you have brought your corporation to a competitive level. That’s great but now we get to data utilization which really gives you the competitive edge.
Analyzation independently utilizes the data that resides inside your platform. It is what tells you how different integrated entities affect each other. For example: what is the connection between social media presence and sales, work hours and employee happiness, room temperature and satisfied customers etc. Analyzation can be done by a third party expert or your own employee. And when you really want to take analyzation to the next level you leave it to the computers. You use AI and machine learning to make the connections between the entities. AI is able to come to conclusions that a normal human couldn’t even have thought about. For example our TVE (shameless plug), does just that. It’s what that tells you: ‘this and this are connected, if you want a better outcome, do something to this’.
The problem with the big picture is that it is one complex entirety. It can even be thought as its own society in the data world. You can’t leave any one of the aforementioned subjects out and hope it’d still manage to work. You want it, you have to get the whole package.
Want to get your big picture in line but wouldn’t want to start making all the steps necessary from scratch? Well, I’ve heard that Tunninen Oy could help you out.