Client testimonial : PwC looks back at the implementation of an internal chatbot

chatbot, internal chatbot, chatbot HR, chatbot IT

PwC France and Maghreb called on dydu in 2018 to create Alex, a conversational robot for employees. Nelly Fercoq, a chatbot project manager at PwC France and Maghreb, looks back at the implementation of the project.

  • Can you describe your company and department ?

PwC provides consulting, auditing, and legal and tax expertise, with the strategic ambition of reconciling businesses, the economy and society. 6,000 employees currently work for PwC in France and North Africa.

I’ve been a member of the IT department for 13 years and have been a chatbot project manager for the last two. I’m responsible for managing and developing the chatbot with another colleague, who is in charge of the knowledge base, reviewing the dialogues and monitoring the analytics and KPIs.

Problems and solutions

  • What problems does the implementation of a concierge chatbot seek to solve ?

Our project was born after interviewing a sample of employees. Our goal was to identify any obstacles in their day-to-day life. This survey revealed in particular that the intranet was seen as dense and complex, and that it was difficult to carry out a search.

We also wanted to help newcomers become autonomous more quickly. Indeed, nearly 2,000 new employees join us each year. The chatbot enables them to understand our whole ecosystem in a simple and quick manner.

To make everyday life easier for employees and to facilitate the onboarding of new recruits, we wanted to implement a tool that could instantly answer all their questions. We decided to deploy an internal chatbot and the project began as a pilot with a handful of employees. We started to feed the bot with knowledge from our intranet. We then launched it throughout the organisation in January 2019.

Project implementation

  • What scope and use cases does your chatbot cover ?

The chatbot is internal. It acts as a concierge and helps employees with various day-to-day issues: HR, IT, office space, events, corporate strategy, etc. For example, it can provide information about how to access payslips, fill out expense reports, request leave, etc. The topics vary but the questions mainly relate to HR and IT.

  • What channels is the chatbot available on ?

The chatbot can be accessed on the internet via an icon on our home page. It is also installed directly on desktops and mobile phones with a web app.

  • What were the different project implementation stages ?

Design – We ran workshops with representatives from each department, with a mix of junior, experienced and senior profiles. We asked them to ask any questions they wanted a quick and clear answer for. This helped us determine which themes to include and the content to create. We also conducted an employee survey to choose the bot’s name; Alex was the most popular of 4 choices.

Building the Knowledge Base – Based on the questions we identified, we collected the official answers from the department representatives. There were 15 of them, divided up by theme. We built a first list of knowledge articles with their answers.

Launch – We communicated a lot when we launched the bot, using all of our internal communication platforms: internal newsletter, cafeteria screens on every level, annual convention, etc. We also presented the solution via a stand during our innovation days, and we always present the chatbot to newcomers during our onboarding programme.

Updates – The number of questions asked is gradually increasing. We add new knowledge articles to a Google Sheet, along with our department representatives. We hold regular calls to clean the knowledge base by deleting or updating any obsolete articles. Every month, we look at the most asked questions with the representatives. My team centralises everything and carries out any updates in the bot management system (BMS) for all the department reps.

  • How did the dydu teams support you in setting up and monitoring the project ?

We assessed various existing solutions. In the end, we chose dydu because of the quality of the BMS, that can be used with many functions by a non-developer, the transparency of pricing, client references and the possibility for on premise of SaaS hosting.

During the implementation phase, dydu’s teams trained us to use the BMS. The aim was to become as autonomous as possible to build knowledge articles and use important functionalities, such as decision trees and variables.

Today, we are fully autonomous. We do however still benefit from dydu support and we have a dedicated customer success manager (CSM) for any questions, update requests or bugs. I’ve had three contacts at dydu since I started working on this project, and I’ve always found them quick to respond. They’re always ready to solve problems and find workarounds when on very short deadlines.

Benefits and good practices

  • What benefits have you seen since implementing the solution ?

When we all began working remotely full time, bot requests increased by 4%. Employees broached new topics as a result of the crisis, which brought about several changes: adjusted working hours for some departments, curfew, guidelines for coming on site, etc.

We updated or adapted a lot of knowledge articles to the situation. We added answers to questions such as, “Who is the Covid rep?”, “How can I get psychological support during the health crisis?”, “Where can I find a permission form if I have to travel for business reasons during curfew?”, or “What are useful Coronavirus contacts?”.

We try to guide our employees as best as possible, so that they can easily find answers during these difficult times. Since the beginning of the year, there are on average 4,000 dialogues per month, with more than 15,500 interactions. More than 300 knowledge articles are used, 136 of which represent 80% of the bot use.

  • Which KPIs do you monitor to steer the bot’s activity ?

We look at the number of dialogues and the number of visitors per day to ensure that employees are still using the bot. When these numbers go down, we communicate about the bot again. We also check the satisfaction rate and review the dialogues between the bot and employees on a daily basis, to make any necessary corrections. We carefully monitor all the KPIs and check the themes to understand employee concerns.

Today, we consider that we have reached our goal. The bot is used regularly, and the satisfaction rate is high. As for any innovative tool, we regularly interview a sample of around 100 employees with different profiles. This enables us to check that our tools still meet their expectations and to identify any new needs.

  • What advice or good practices do you have about the relevance , use and management of the bot ?

If the chatbot cannot answer an employee’s questions several times, they are unlikely to return. I therefore recommend having all the necessary resources internally, to offer the best possible service. This involves reading the dialogues, adding matches, and creating new knowledge articles. We pay particular attention to the quality of the answers we provide, to ensure that they are precise and current.

Alex also has its own email address. We make a note of the name of any employees with unanswered questions and reply a little later by email. This is particularly appreciated internally.

  • Why would you recommend the dydu solution ?

Using the BMS to add knowledge articles is very clear. The tool is easy to use because it is very intuitive. Everything is simple, clear, and quick for end-users too. All our contacts are accessible and friendly. Our CSM is very responsive. We know that we can contact her if we have a problem. Dydu immediately takes our issues on board and finds a solution. I also really appreciated the exchange workshops with other dydu clients about developments we would like to see for the software; very few publishers do this.

Next steps …

  • What prospects or developments do you have planned for the projetc ?

The next step will be to interface the chatbot with some of our HR tools so that it can provide fully personalised answers. The chatbot is already connected to our authentication system, which means Alex can address employees by their first name. We’re also working on personalising the answers according to the employee’s site location, ranking and service line.