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The Future of Business Intelligence
Overloaded Dashboards and complicated Reports belong to the past. You will soon be able to ask your âDecision Support Digital Assistantâ all the challenging questions and get back answers, not just data.
Imagine if you could simply ask your digital assistant any question about your business; and get answers, not just data. In the not so distant future, you will be able to engage in progressive business conversations with your âDecision Support Digital Assistantâ.
For example, if you simply ask: âHow is my product performing?â the system will:
1. Understand who is asking
The system identifies the user asking the question and retrieves the context (role, experience, perspective in the company, history of interactions, history of meetings and planning etc.). User identification happens seamlessly via multiple signals, including voice, location, input from the connected building etc. This is used for setting the context and personalizing the responsesâââfor the same question, a sales person will get different answer from an engineering manager.
2. Identify the referenced âproductâ
The system analyzes the business question with NLP algorithms. By using the knowledge it has about the company (context, products, services offered, organizational structure, activity, performance, market, competition etc.), the system derives what the âproductâ in the original question refers toâââwithout even naming it. It then retrieves metadata, context, insights and knowledge about the productâââto be used in determining what âperformanceâ means for the particular product, what metrics and KPIs are available and what content is available in the public domain.
3. Identify âperformanceâ, retrieve KPIs & data index
The system will recognizes that the question refers to âperformanceâ and load all the metadata and indexes pointing to âproduct performanceâ assessmentâââinsights, KPIs and other analytical elements.
4. Derive the perspective of the business question
By using also the history of interactions with the specific user (and similar ones), it can derive the perspective of the questionâââfor example âproduct performanceâ means different things to different people in the same company: for a sales manager, it means sales volume, revenue, leads, conversion rates etc; for a quality manager, it means overall customer satisfaction score, quality metrics; from a CEOâs point of view its all about product profitability.
The âDecision Support Digital Assistantâ will combine all the above, to synthesize the right business answer and initiate an engaging, personalized business conversation.
The business being answers synthesized by the Decision Support Digital Assistant, may include not only internal statistics and insights, but also externalâââpublic domain content- enriching the actual response. For example, in the question âhow is my product performing?â the DSDA will attempt to locate relevant news about the product, social threads, references, complaints or other public-domain content about the specific product and similar onesâââincluding competition.
By using this holistic approach, the âDecision Support Digital Assistantâ may reply to the sales person asking the âhow is my product performingâ question, with more sophisticated, responses like:
âYour product âAâ is doing great, with a seasonally adjusted increase of sales 5% in your territory. Be aware though that there is an increasing online criticism due to quality issues of feature âBâ. I have also e-mailed you a recently published patent application on a similar technologyâ
The user could follow-up and ask for more details or certain actionsâââall via voice; the DSDA may also present suitable insights on the nearest connected screen to the user asking the questionâââupon confirmation.
Business Intelligence systems of the future will provide answers, not just data. The complexity of analyzing data will be hidden under next generation NUI experiences. Insights and data stories will be incorporated in the right format, for the specific user and timingâââto support or explain the business responses provided.
Referenced patent application: US 15/357574 20180144064
The future of Business Intelligence was originally published in Hacker Noon on Medium, where people are continuing the conversation by highlighting and responding to this story.
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