IBM Business Assistant

IBM Business Assistant

Mobile, Desktop

SaaS

Overview

Overview

IBM Business Assistant helps you stay on top of your business-critical workload and proactively notifies you of changes to recommends steps for successful task completion.
I have worked as a UX Designer during my internship & working student contract at IBM Studio, Germany as part of the Cloud Services team on building this project.

IBM Business Assistant helps you stay on top of your business-critical workload and proactively notifies you of changes to recommends steps for successful task completion.
I have worked as a UX Designer during my internship & working student contract at IBM Studio, Germany as part of the Cloud Services team on building this project.

Problems

Problems

The whole design team assisted our design researcher with extensive user research. I interviewed participants with different management roles within the internal IBM Studio. In total we did 120 survey participants to gain insights about their day-to-day work, productivity issues and workarounds.
Below are some of the main uncovered problems.

The whole design team assisted our design researcher with extensive user research. I interviewed participants with different management roles within the internal IBM Studio. In total we did 120 survey participants to gain insights about their day-to-day work, productivity issues and workarounds.
Below are some of the main uncovered problems.

One of the challenges was to understand the tool landscape in the enterprise or bigger size companies and how it is applied across different job roles for different needs.

Before I delivered the user authentication flow there were more use cases that belonged in the onboarding flow such as the coupon offering for first- time users and the onboarding slideshow.

To better understand the product management workflow we interviewed internally across different management roles and departments. We found it challenging to define a specific worklow.

To better understand the product management workflow we interviewed internally across different management roles and departments. We found it challenging to define a specific worklow.

Staying up to date with innovative products while having real-time data availability for easier decision making was another recurring identified pain point.

Staying up to date with innovative products while having real-time data availability for easier decision making was another recurring identified pain point.

How might we better support business professionals to simplify their workflow ?

How might we better support business professionals to simplify their workflow ?

Goals

Goals

The project aimed to cover the following aspects

The project aimed to cover the following aspects

This project began from the ground up, with no existing software, which is unusual within IBM. The scope was quite broad, so before the team scheduled a design thinking workshop, we did some preliminary research to have a deeper understanding of the problem area.
I also looked into our competition to better understand opportunities.

Besides getting the green light from stakeholders we aimed to get the design in front of the target users to make sure we are heading in the right direction. I worked on prototyping different solutions and cca 10 users was used for each persona. This enabled us to validate changes from different angles and get a more complete picture.

Besides getting the green light from stakeholders we aimed to get the design in front of the target users to make sure we are heading in the right direction. I worked on prototyping different solutions and cca 10 users was used for each persona. This enabled us to validate changes from different angles and get a more complete picture.

Besides getting the green light from stakeholders we aimed to get the design in front of the target users to make sure we are heading in the right direction. I worked on prototyping different solutions and cca 10 users was used for each persona. This enabled us to validate changes from different angles and get a more complete picture.

My role in the larger team was to assist in the discovery phase and work on potential design solutions through wire-framing and iteration.
We’d have a daily scrum and a weekly meeting where we’d discuss the design and development.

Many of those sessions focused on cross-functional collaboration and team alignment, and we had to negotiate and postpone key features for MVP+1 on a number of occasions.

• new users need a fast and secure user signup in order to use the app as soon as possible to order a ride-sharing car

• have a seamless experience both on iOS and Android

Another challenge was understanding the tool landscape in the enterprise and how it is applied across different job roles for different needs.

Another challenge was understanding the tool landscape in the enterprise and how it is applied across different job roles for different needs.

We concluded that including predefined workflows for different job roles and tasks as well as the option to customize them and create them from scratch is a good direction.
We looked into and integrated areas like Business Productivity, Sales, Collaboration, Marketing, Banking, Time Tracking, Customer Relationships and Team Management.

We concluded that including predefined workflows for different job roles and tasks as well as the option to customize them and create them from scratch is a good direction.
We looked into and integrated areas like Business Productivity, Sales, Collaboration, Marketing, Banking, Time Tracking, Customer Relationships and Team Management.

The users can also create their own custom solutions. They have the option to integrate tools like Watson’s artificial intelligence which is a search and text-analytics platform that can retrieve information buried inside enterprise data.

The users can also create their own custom solutions. They have the option to integrate tools like Watson’s artificial intelligence which is a search and text-analytics platform that can retrieve information buried inside enterprise data.

Design process

Design process

Our bigger team and stakeholders explored design solutions broadly. For team alignment we clarified the user goals we were designing for. These were that the assistant should understand a situation, prioritise, notify the user and help completing the task.

Our bigger team and stakeholders explored design solutions broadly. For team alignment we clarified the user goals we were designing for. These were that the assistant should understand a situation, prioritise, notify the user and help completing the task.

We explored how this would look within a customisable dashboard split into main activities cards.

This would give the user an overview on areas like: tasks that need priority, relevant information such as news, project status or involved people.

We also explored bringing more visibility to important emails, project notifications or missed client calls.

We explored how this would look within a customisable dashboard split into main activities cards.

This would give the user an overview on areas like: tasks that need priority, relevant information such as news, project status or involved people.

We also explored bringing more visibility to important emails, project notifications or missed client calls.

Final designs

Final designs 

We explored how this would look within a customisable dashboard split into main activities cards.

This would give the user an overview on areas like: tasks that need priority, relevant information such as news, project status or involved people.

We also explored bringing more visibility to important emails, project notifications or missed client calls.

I collaborated with the team in deciding the most basic features needed for the product to launch. The coupon offering and the onboarding slideshow were left out, at this stage. What was kept was only what allowed for the product to be deployed, excluding non essential features.

After exploring how we can bring visibility within a dashboard for the activities involved in managing projects such as prioritising tasks, news project status or involved people - the direction changed.

Driven by the core feature capability of creating flows that integrate apps, services and Watson capabilities - the dashboard was built as a feed.

This allowed to bring visibility to the insights brought from the activated flows or “Skills”.

This solution prioritised the technical feasibility since it was easier to fetch the insights from the implemented active flows and also had the user impact of supporting the user to finish tasks.

After exploring how we can bring visibility within a dashboard for the activities involved in managing projects such as prioritising tasks, news project status or involved people - the direction changed.

Driven by the core feature capability of creating flows that integrate apps, services and Watson capabilities - the dashboard was built as a feed.

This allowed to bring visibility to the insights brought from the activated flows or “Skills”.

This solution prioritised the technical feasibility since it was easier to fetch the insights from the implemented active flows and also had the user impact of supporting the user to finish tasks.

Further product iteration

Further product iteration

The problem spectrum was more broad initially. Even though the product discovery defined the main problems to deliver solutions and implement the IBM Business Assistant, I also had the chance to explore further opportunities during my master thesis as a working student.

The problem spectrum was more broad initially. Even though the product discovery defined the main problems to deliver solutions and implement the IBM Business Assistant, I also had the chance to explore further opportunities during my master thesis as a working student.

The goal of the master thesis was to further uncover pain points within the digital workers’ workflows and leverage further IBM Watson AI capabilities to potentially solve them.

So this is a direction that I went on to explore further.

The goal of the master thesis was to further uncover pain points within the digital workers’ workflows and leverage further IBM Watson AI capabilities to potentially solve them.

So this is a direction that I went on to explore further.

The conversational interface, integrated within collaborative chat or voice was an initial idea explored early on that I worked on and prototyped for initially in the discovery and ideation stage during my internship.

However it ended up outside of the scope of the project for the release at the time.

Initially it was integrated within the app and the conversation was between the user and assistant directly.

The conversational interface, integrated within collaborative chat or voice was an initial idea explored early on that I worked on and prototyped for initially in the discovery and ideation stage during my internship.

However it ended up outside of the scope of the project for the release at the time.

Initially it was integrated within the app and the conversation was between the user and assistant directly.

One of the research findings that I considered is that a big part of the workflow for digital workers and tasks, and decision are spread through conversation apps such as Slack.

So I realised that there is a missed opportunity for the IBM Watson AI assistant to support the conversation and needed tasks within apps like Slack directly.

Since the common denominator was actually the input typing area, using the language processing Watson capabilities to support being on top of tasks directly within conversations made a lot of sense to explore.

One of the research findings that I considered is that a big part of the workflow for digital workers and tasks, and decision are spread through conversation apps such as Slack.

So I realised that there is a missed opportunity for the IBM Watson AI assistant to support the conversation and needed tasks within apps like Slack directly.

Since the common denominator was actually the input typing area, using the language processing Watson capabilities to support being on top of tasks directly within conversations made a lot of sense to explore.

With the language processing AI the user can be supported to search for articles more easily within the conversations with the team, without switching apps.

With the language processing AI the user can be supported to search for articles more easily within the conversations with the team, without switching apps.

Based on the uncovered pain point of wasting time to uncover information I considered the opportunity to find relevant files within the conversation.
For this the solution to integrate tools like Watson’s artificial intelligence to use search and text-analytics in order to retrieve information buried inside enterprise data made it a technically feasible option.

Based on the uncovered pain point of wasting time to uncover information I considered the opportunity to find relevant files within the conversation.
For this the solution to integrate tools like Watson’s artificial intelligence to use search and text-analytics in order to retrieve information buried inside enterprise data made it a technically feasible option.

Similar to how specific task flows were automated through the IBM Business Assistant platform, users would be able to access and adjust the flows directly within the conversation.

Similar to how specific task flows were automated through the IBM Business Assistant platform, users would be able to access and adjust the flows directly within the conversation.

The integration in tools like Slack or messenger apps made sense since cross collaboration happens within conversation platforms.
Here, the design solution for sharing headlines, tracking a topic or saving it to a project is explored.

This design solution that uses AI Watson in cross collaboration within a conversation, can make these actions contextual as the conversation unfolds.

The integration in tools like Slack or messenger apps made sense since cross collaboration happens within conversation platforms.
Here, the design solution for sharing headlines, tracking a topic or saving it to a project is explored.

This design solution that uses AI Watson in cross collaboration within a conversation, can make these actions contextual as the conversation unfolds.

Product evolution

Product evolution

Further on from IBM Business Assistant, IBM Watson Orchestrate was further developed.

It integrated conversational interface and made use of Watson AI’s capabilities in detecting sentiment in language among other features.

It was interesting to see how this feature was initially discarded and shaped the product strategy later on,
Happy to see that our work wasn’t wasted :)

Further on from IBM Business Assistant, IBM Watson Orchestrate was further developed.

It integrated conversational interface and made use of Watson AI’s capabilities in detecting sentiment in language among other features.

It was interesting to see how this feature was initially discarded and shaped the product strategy later on,
Happy to see that our work wasn’t wasted :)

↗ “5 Things to Know About IBM’s Watson Orchestrate”

↗ “5 Things to Know About IBM’s Watson Orchestrate”