<\/p>\n\n\n\n
The classic Business Intelligence formats – dashboards and\nreports – have been useful for monitoring the business, but are rarely\nsufficiently intuitive to make proactive decisions. Business Intelligence\nhas always been retrospective, looking back over events that have already taken\nplace. The technology just about guides the only-human user, solely giving them\nthe facts and dumping the more stressful work – analysis – in their lap.<\/p>\n\n\n\n
What if we add Predictive Analysis? The name alone describes\nits forward-looking approach and it\u2019s a field falling within Artificial\nIntelligence. Algorithms extract patterns of existing data and project\nthem forwards. These patterns are often deeply hidden and difficult to deduce\njust by looking. Predictive Analysis enables successful optimisation of many\nbusiness scenarios, by calculating credit ratings in finance; stock levels in\nmanufacturing; room bookings that are going to be cancelled; the consumption of\na specific customer, and much more.<\/p>\n\n\n\n
So, what\u2019s the problem? Simply that Predictive Analysis is\nstill a specialist field which, in the majority of cases, needs tools which are\nnot designed for normal business users. As a result, they are two separate\nworlds which are difficult to integrate and frequently require a huge effort by\nthe business to understand the implications they bring based on the statistical\nmethods involved.<\/p>\n\n\n\n
The truth is that human beings are not ready for purely statistical\nreports or statistical models.<\/p>\n\n\n\n
Instead, we pay attention to, and remember, narratives which\nhave direction and flow. Inside our heads, we do not picture the world as data\nstructures and algorithms, but instead as stories with structure and character,\neven when dealing with abstract concepts. This is just like a seller who may\nhave difficulties in reaching their targets and products that may have\ndifficulties in reaching and surpassing the theoretical barriers of the budget\nset. This is a narrative, not an analysis, that finds out why.<\/p>\n\n\n\n
However, we are also good at taking in new information,\nirregularities and warnings quickly. Patterns and exceptions jump out with\nremarkable clarity, as we get to understand the business and learn to detect\nchanges. We pay attention to alerts and are sensitive to changes in regular\npatterns.<\/p>\n\n\n\n
So, how are we going to make the most of these different\ncognitive styles when making business decisions?<\/p>\n\n\n\n
Fortunately, new technology and viewing techniques, and\nMachine Learning, allow us to integrate the best of Business Intelligence into\nPredictive Analysis and the creation of human common sense. The task consists\nof bringing together, with a gentle touch and in a single environment, the\nvarious ways in which human cognition and machine analysis, generally\nconsidered to be separate techniques, can work together. This is technically\nknown as Augmented Intelligence, as the high computational capacity of machines\ncan help us make decisions.<\/p>\n\n\n\n
In the first place, users must be capable of building\nNarratives. Instead of presenting the results in a dry, static way, it is\nreally useful to be able to build a narrative which flows from one observation\nto another and from queries to decisions, supported by effective data and\ngraphics. Users and their colleagues should be able to go into the details in\ndepth, as good visuals pose new questions instead of being limited to illustrating\nresponses. It is also important that this is done in a much more interactive\nstyle than slide presentations or a cooked-up Excel (which doesn\u2019t allow any\ndetail to be gone into). The answer to any good business question is definitely\nnot \u201cmore PowerPoint\u201d.<\/p>\n\n\n\n
Narratives are excellent for communication and\ncollaboration, but we also need to pay attention to the signals which jump out\nabout changes to our position. Predictive Analysis can help here, but only if\nit is perfectly integrated into our usual tools. Technology should work\nwith our business know-how, without the need for theoretical experience, whilst\nincluding hidden attributes that we ourselves cannot find in the volume and\ncomplexity of business data today.<\/p>\n\n\n\n
At Mind Analytics we work to democratise Artificial\nIntelligence. All businesses can benefit from Predictive Analysis as an\naccessory to their Business Intelligence dashboard. You don’t need to be Google\nor Amazon to have a great team of data scientists available to make this change.\nNowadays there are simple tools which can give us much more value in making\ndecisions, changing the centre of gravity towards a more predictive view which\nallows users to be ready for what is coming.<\/p>\n\n\n\n
We are ready to help you make this change. We can work\nalongside you from the beginning to define strategies to follow and also if you\nalready sure about what you want, but not how to do it. Are you ready?<\/p>\n","protected":false},"excerpt":{"rendered":"
The classic Business Intelligence formats – dashboards and reports – have been useful for monitoring the business, but are rarely sufficiently intuitive to make proactive decisions. Business Intelligence has always been retrospective, looking back over events that have already taken place. The technology just about guides the only-human user, solely giving them the facts and dumping […]<\/p>\n","protected":false},"author":1,"featured_media":1326,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[29,31],"tags":[],"class_list":["post-1373","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-mind-in-action-en","category-technology"],"yoast_head":"\n