# The Future of Business Intelligence is … Voice

> 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 timing.

- Author: [George Krasadakis](https://theinnovationmode.com/george-krasadakis)
- Published: 2021-12-11
- Topic: [AI strategy](https://theinnovationmode.com/the-innovation-blog/topic/ai-strategy)
- Source: https://theinnovationmode.com/the-innovation-blog/the-future-of-business-intelligence-is-voice

![The Future of Business Intelligence is … Voice](https://theinnovationmode.com/media/blog/the-future-of-business-intelligence-is/chart-gf8dd829de-1920-1500w.webp)

> *Overloaded dashboards and complicated reports belong to the past. We will soon be able to ask our ‘Decision Support Digital Assistant’ 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 ‘**Decision Support Digital Assistant’**.

For example, if you simply ask:

## ‘***How is my product performing?***’

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 responses — for the same question, a *salesperson* will get a different answer from an *engineering manager*.

## **2. Identify the referenced entities **- the ‘product’ in this example

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 **‘product’ **in the original question refers to — without even having to name it. It then retrieves metadata, context, insights, and knowledge about the identified product — to be used in determining what ‘performance’ means for the particular product, what metrics and KPIs are available, and what content is available in the public domain.

## **3. Estimate the ‘performance’, retrieve KPIs & data index**

The system recognizes that the question refers to ‘**performance**’ and loads all the metadata and indexes pointing to ‘product performance’ assessment — insights, 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 question — for example ‘product performance’ 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 **CEO’s **point of view its all about product profitability.

> *The ‘Decision Support Digital Assistant’ 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 external — public domain content- enriching the actual response. For example, in the question ‘**how is my product performing?**’ 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 ones — including competition.

By using this holistic approach, the ‘**Decision Support Digital Assistant’ **may reply to the salesperson asking the ‘*how is my product performing*’ question, with more sophisticated, responses like:

> *“Your product ‘A’ performs well, 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 ‘B’. I have also e-mailed you a recently published patent application on a similar technology”*

The user could follow-up and ask for more details or certain actions — all via voice; the DSDA may also present suitable insights on the nearest connected screen to the user asking the question — upon confirmation.

**Business Intelligence **systems of the future will provide *answers*, not just data. The complexity of analyzing data will be hidden and the experience will be driven primarily via voice. Insights and [**data stories**](https://theinnovationmode.com/the-innovation-blog/data-driven-companies-and-the-importance-of-a-data-culture) will be incorporated in the right format, for the specific user and timing — to *support* or *explain* the business responses provided.

**Referenced patent application**: US 15/357574 20180144064