Data. Consulting. Analytics. Technology.

Tag: competitive edge

Artificial Intelligence, Hospitality

Innovation- Chatbots in the Hospitality Industry

Chatbots were one of the most significant trends of 2017. These small pieces of software with pre-programmed interactions allow you to communicate with them naturally and simulate the behavior of a human being within a conversational environment. It can be a standalone service or integrate within other messaging platforms like Facebook Messenger.
The adoption of these virtual assistants is growing, and brands are using chatbots in lots of exciting ways. You can order food, schedule flights and get recommendations for pretty much anything. Chatbots seemingly are the future of marketing and customer support.
The use of chatbots in the hotel industry is still evolving, but it currently encompasses a wide range of services, from hotel bookings and customer service inquiries to pre/post-stay inquiries and general travel advice.
The hotel industry can experience many benefits from the use of chatbots, among them:
  • They can be used as a reservation channel to increase direct bookings.
  • Since chatbots are available 24/7, they will reduce reception workload by giving guests instant and helpful answers around the clock.
  • Guests can check-in/check-out on the fly with the aid of a chatbot.
  • They will help independent hotels to build accurate guest profiling so that they can provide personalized offers to their guests. The hotel will be able to deliver tailor-made offers instantly and directly via chat before, during or after their stay.
  • Guests can opt-in to be notified from chatbots about the places to visit, the rates of the hotel’s cars, etc.
  • The ease of booking and the proactive concierge services create brand loyalty and improve guest satisfaction.
  • Hoteliers will be able to obtain customer reviews post-stay via a chatbot. This is much less invasive compared to traditional email marketing, which is often ignored.
What challenges do they pose for hoteliers?
Adopting this new hotel technology involves many challenges for hoteliers. For instance:
  • Independent hotels will need to simplify their booking process to accommodate chatbots.
  • Hoteliers will need to provide a consistent booking experience on chatbots in comparison to other channels.
  • General managers will need to monitor chatbots where there is a human element. They will need to allocate staff resources.
  • Hoteliers will need to manage guest expectations since guests will expect a quick turnaround on their requests through chatbots.
As you can see, chatbots present many opportunities for hoteliers, from increasing customer loyalty to enhancing the guest experience. To keep your guests coming back for more, definitely consider joining the chatbot revolution – but only if your hotel is equipped and prepared for this big step.
Business Intelligence

Smart City, Smart People, Smart Data

Smart City, Smart People, Smart Data

Creating a smart city is based on concepts of innovation, technology, sustainability and accessibility ensuring economic progress as well as a higher quality of life. This is opening an infinite number of opportunities to become more efficient in both public and private management. It means that  both the public sector, as well as the private (all types of business)  sector have to be prepared to express their ambitions collaboratively about what they want to achieve in the future. 

Democratisation of technology has meant that people are much more demanding, informed, über-connected and multi-channel. With the advent of new technologies in particular Internet of things, new business models are emerging to  build solutions that increase or improve  the citizens’ quality of life. from optimising public transport routes to using smart garbage bins to track litter habits.

Whilst the deployment  of smart cities involve several innovative technologies to facilitate sustainable urban spaces, the concept is still vague and open.  The ‘smart’ capabilities need to be operational and measurable. In order to evaluate how ‘smart’ is a smart city, robust data management and analysis is required.

This entails very close collaboration between both public and private sectors to share and analyse the vast amount of data being generated by new technologies. There are a billion places to gather data, and more tools are coming to market to help collect as much of it as possible.

The ability to share vital information in real time would enable businesses operating both in the private and public sector to develop powerful hardware systems  and software solutions;  that not only support automation but provide the ‘smart’ capabilities of a city and its infrastructure. Today, there’s an assortment of technologies being used to handle various characteristics, such as high volume, data location, and a variety of data source types. The collection of crucial data from any kind of source, such as the own city’s sensors, participatory sensing (for instance, sensors integrated in citizens’ smartphones), would enable the compilation of information about people and vehicle traffic, parking, environmental values, waste generated, energy consumption and healthcare etc.  for the smart functioning of the city’s basic services.

It’s easier said than done one is tempted to say. Whatever the hype, whether artificial intelligence, machine learning or automation, it must start with data. Data is vital for smart cities technology.

First and foremost sound and mature data management practices  need to be in place. Technology alone is not sufficient to build a smart city. Competent human intelligence is also part of the equation to complete this:  Employees need to be comfortable analyzing and making decisions with data. Not only should the data analytics platform be robust, the team’s responsible for it must have a good mix of skills. The tecchies and fuzzies of this world will drive the vision of the Smart City not the traditional analysts.

“Finding solutions to our greatest problems requires an understanding of human context as well as of code; it requires both ethics and data, both deep thinking people and Deep Learning AI, both human and machine; it requires us to question implicit biases in our algorithms and inquire deeply into not just how we build, but why we build and what we seek to improve.” * (Scot Harley )

The essential question in the continuously growing amount of data volumes is how to make practical use of these volumes and without analytics, interpretation and algorithms it just isn’t possible. Advanced analytics has emerged as a critical component of modern analytics architecture, with companies turning to statistics, predictive algorithms, and machine learning to maximize the value of very large data sets. Without having to examine every dimension and variation in the data manually, people are automatically guided to relevant insights and alerted to data points that are worth exploring. The use of AI-driven smart data for customer analysis, fraud detection, market analysis, and compliance is becoming a reality to uncover insights hidden in data.

Investing in a strong modern analytics platform leverages the partnership between Business and  IT . When business users are given tools to analyze data on their own, they are free to answer questions on the fly, knowing they can trust the data itself. This leads to accurate, agile reports and dashboards and one single version of truth. And IT, free from dashboard and change requests, can finally prioritize the data itself: safeguarding data governance and security, ensuring data accuracy, and establishing the most efficient pipelines for collecting, processing, and storing data.

Adapting to a scenario that is extremely technologically, economically and socially dynamic is the lynchpin of  development and helps to drive smart systems geared towards improving integration and interaction of the smart citizen.

When data is approached intelligently to generate insights into how the  tech systems are performing it is only then that efficiencies and savings could be measured across all strategic elements of Smart Cities -enterprise competitiveness, mobility, urbanism, energy, water, waste recycling, security, culture and healthcare.

Self-service Analytics

Track profit, loss with an intuitive CFO dashboard

This CFO dashboard combines complex profit-and-loss data into one page that’s anything but. The top two views provide an overall picture of quarterly and yearly performance over the past three years. The views include key financial measures such as net sales, net profit, and net profit margin. Whether you want to view your numbers according to region, channel, customer segment, or product category, the results are right at your fingertips.

Click on the link below and be amazed by this dashboard . It’s just a click  away!!

https://www.tableau.com/solutions/workbook/cfos-overview-business

 

Happy to have a chat with you to share ideas, discuss opportunities or even prepare a demo for you . Contact us on info@businesslab.mu.

Data Governance, Data Regulations

GDPR and Data Governance: A hand in hand affair

The introduction of GDPR should not be seen as a burden for companies but rather as an opportunity to review all the data governance policies that are in place. Companies should be able to find the right balance between GDPR and their data governance structure.

Companies could create a competitive edge by not only addressing how they manage the personal data but for all the data they hold. If companies get it right, they could discover new business opportunities waiting to be exploited.

As we all know by now, the GDPR gives every EU citizen the right to know and decide how their personal data is being used, stored, protected, transferred and deleted.

Those companies that put data privacy at the forefront of their business strategy would be the ones who are clearly and efficiently managing their customer data in a fair and transparent way. Hence giving them the competitive edge based on privacy.

One of the requirements of GDPR is to document what personal data is held, where it came from and who is it shared with. By really understanding the data they hold, companies could be made aware of the data they can gather, as well as analyse and apply this data to boost sales or marketing efforts.

Companies should ensure that their data governance structure will support the GDPR requirements. Policies and procedures need to be created or re-assessed to help keep corporate data consistent and ensure that it meets the information needs of business users. It is also an opportunity to review data management practices.

The GDPR requirements combined with a robust data governance structure could give organisations the opportunity to become a data-driven company based on building tools, abilities, and a culture that acts on data hence really making an internal transformation around data.