[et_pb_section fb_built=”1″ _builder_version=”4.20.4″ _module_preset=”default” custom_padding=”0px||0px||true|false” locked=”off” global_colors_info=”{}”][et_pb_row column_structure=”1_2,1_2″ _builder_version=”4.17.6″ _module_preset=”default” width=”100%” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.17.6″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.7″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n
You know data is a priority. But do you know what your next AI investment will cost you if your data is not ready for it? <\/p>\n
In two weeks you know where you stand: your data maturity, honestly assessed, and a concrete action plan. So you make your next AI investment with the facts on the table: you know which applications are feasible today and which need data work first. Not a score out of ten, but a prioritised list and a sequence. A no-go is also an outcome.
\n[\/et_pb_text][et_pb_button button_url=”https:\/\/juvo.be\/en\/get-in-touch\/” url_new_window=”on” button_text=”Book an introductory call” _builder_version=”4.27.7″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_button][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.17.6″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/juvo.be\/wp-content\/uploads\/\/Gemini_Generated_Image_8kqwip8kqwip8kqw-1024×682.jpeg” alt=”Artificial neural networks, ANN, connectionist systems. Abstract simple graphics scheme of neural machine mind with AI. Artificial intelligence, cybernetic net in computer learning. Science concept. ” title_text=”Gemini_Generated_Image_8kqwip8kqwip8kqw” _builder_version=”4.27.8″ _module_preset=”default” border_radii=”on|6px|6px|6px|6px” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.20.4″ _module_preset=”default” background_color=”RGBA(255,255,255,0)” custom_padding=”0px||0px||true|false” locked=”off” global_colors_info=”{}”][et_pb_row make_equal=”on” _builder_version=”4.17.6″ _module_preset=”default” width=”100%” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.17.6″ _module_preset=”default” global_colors_info=”{}”][et_pb_text admin_label=”Tekst” _builder_version=”4.27.7″ _module_preset=”default” background_color=”#F2F2F2″ min_height=”100%” custom_padding=”25px|25px|25px|25px|true|true” border_radii=”on|6px|6px|6px|6px” global_colors_info=”{}”]<\/p>\n
This AI readiness assessment runs over two weeks. Short enough not to stall, long enough to look properly. <\/p>\n
In week one we talk to the people who know. Depending on your organisation, that means operations, finance and IT. We map which systems you use, which data sits where, who is accountable for what, and where it hurts.
We also look at how your systems are connected, how reliable the data in your source systems is, and the current state of your reporting. <\/p>\n
By the end of that week you already know more about your own data than when we started.<\/p>\n
From that intake we assess your data maturity across four dimensions: quality, accessibility, governance and integration. From there follow the priorities and the order. <\/p>\n
There are online questionnaires that give you a data maturity score in a couple of minutes. They give you an indication. We do something else: we talk to your people, look inside your systems, and deliver a prioritised list and a sequence.
\n[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.20.4″ _module_preset=”default” custom_padding=”0px||0px||true|false” locked=”off” global_colors_info=”{}”][et_pb_row admin_label=”Row” _builder_version=”4.17.6″ _module_preset=”default” width=”100%” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.17.6″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.7″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n
It fits if this sounds familiar:<\/p>\n
– You know data is a priority, but not where you stand.
\n– You want to start an AI project and first need to know whether your data can carry it.
\n– You have structural problems with your reporting: figures in your Power BI reports that do not add up, reports that contradict each other. Usually the dashboard is not the problem. The data underneath it is.
\n– You want to set up a data warehouse, a data team or a strategy and do not know where to start.
\n– You need an impartial analysis to win internal commitment for a data investment.<\/p>\n
Not a fit if:<\/strong><\/p>\n – you do not yet use any digital systems: paper-based invoicing, no ERP. If that sounds like you, the next question is what you get after those two weeks. In two weeks, this is what you get:<\/p>\n
\n– you are looking for a technical implementation without the strategic analysis.<\/p>\n
\n[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.20.4″ _module_preset=”default” custom_padding=”0px||0px||true|false” locked=”off” global_colors_info=”{}”][et_pb_row admin_label=”Row” _builder_version=”4.27.7″ _module_preset=”default” width=”100%” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.17.6″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.7″ _module_preset=”default” global_colors_info=”{}”]<\/p>\nWhat you get<\/h2>\n