On this website we use cookies that are strictly necessary to make our website function correctly, as well as optional – analytics, performance and/or marketing - cookies which help us improve our website by collecting and reporting information on how the website is used, as well as help us to reach out to you with information about our organization or offer. If you do not wish to accept optional cookies when visiting our website, you may change the settings in the Cookie Settings. For more information go to Cookie Settings.

Skip to content

Business at the Speed of Data

Business

Aug 10, 2020 - 6 minutes read

Thumbnail 5 Data Visualisation Best Practices 416X305
Michał Zgrzywa AI Director

AI Director at Objectivity, experienced manager, software developer at heart. 

See all Michał's posts
Data Driven Organisation Blog Ebook 416X300

Share

Data and Artificial Intelligence have brought about remarkable possibilities. Algorithms can analyse pictures and videos to recognise and localise objects, people and even their emotions. Simulation algorithms can test millions of potential future scenarios to find the most optimal one. Intelligent dashboards are able to summarise complex data, recognise trends, and find anomalies. Algorithms can recommend which actions to take and which products to build, increasing customer satisfaction and informing business decisions.

However, although our world is changing and we’re witnessing plenty of great success stories, for many, there are still areas to improve upon. In a recent inspiring Forrester report, we read that the need to become insights driven is universally recognised: 90% of data and analytics decision makers see increasing the use of data insights in business decision-making as a priority. At the same time, however, many organisations are struggling to do just that: 91% of respondents report that improving the use of data insights in decision-making is challenging for their organisations.

Why are companies still finding it challenging to drive their business with data with all the ready-to-use technology, certifications, and talent pool available on the market?

There’s no one single root cause for this – it’s likely due to a good old mixture of technology, processes, and people. However, when talking to our clients, we noticed that what often helps is to visualise the change that needs to take place in order to become more data-driven as a journey.

This article describes which kinds of steps your organisation could take to become ready to derive business value from data.

data_engineering_graph

We believe that to generate value from your data, you must first have a solid foundation in place—a proper engineering approach to manage your data.

When your data is well-handled, you’ll have limitless possibilities to achieve greater business and social value. Data allows your business to gain valuable insights. Standard tools and methods such as business intelligence (BI) and data visualisation can be used to provide insights and high-level summary information as well as identify trends. The process of employing BI is relatively quick and straightforward and can provide valuable input, which can be leveraged during decision-making, target-setting, and prioritisation.

The most common business benefits of being able to take advantage of reports, dashboards, and trends include:

  • Gaining operational insights by being able to understand your business thanks to having access to up-to-date operational and financial dashboards and visualisations,
  • Uncovering points of interest, which may result in improving the quality and accuracy of your business by enabling you to recognise patterns and to spot anomalies.
  • Improved planning by applying advanced simulation and forecasting models.

But data insights are only the first step. Once you can trust your data, having access to data insights will lead to better decisions and actions. This requires not only technology (e.g. recommendation engines) but also that your business is ready to embrace new ways of leveraging data and understands that the technology assists, not replaces.

Whether you work on the business side or in IT, one thing’s certain—building understanding between these two areas is absolutely crucial when it comes to handling data.

For instance, how should one measure the quality of data? We’ve seen scenarios in which the number of delivered dashboards was a big thing. Everyone seemed happy. The IT department was content because the visualisation of the data was neat, and no performance issues appeared. And business stakeholders were satisfied because they asked for a dashboard and they got one. But, wouldn’t it be better to measure how many decisions were actually made or changed because of the information provided by the dashboards?

Business stakeholders need to feel comfortable in interpreting the data. It’s about much more than asking them, “What kind of dashboard do you want?”. A much better approach would involve asking, “What worries you the most in making your day-to-day decisions?”. Once the challenge is clear for everyone, it’s time to start thinking about which kind of data insights will be able to help and what type of processing is needed to achieve the result.

And finally, because this is not the end of the data road, the solution provider will need to make sure that business stakeholders are able to easily interpret the data so as to inform their decision-making process with its insights. It’s the solution’s role to explain where the data came from, what happened to it, and what kind of issues came up.

There are several useful approaches on the market that can help you to make data-driven decisions, including explainable AI or explainable analytics. They all have one common denominator— i.e. to enable organisations to make decisions based on data, one must first put in the effort to tell the story right. And once you’ve convinced your data users, you’ll be able to take advantage of many new value-adding optimisations.

And, finally, when your organisation becomes truly data-driven, you’ll be able to reap a range of business benefits:

  • Automated recommendation engines can significantly optimise work. They can help your people to include multiple perspectives into their decision-making process by enabling them to utilise historical data and forecasting. This way, you’ll be able to make crucial business decisions in a much more fitting, informed manner.
  • Additionally, recommendation engines can assist your people in making repetitive decisions, so that they can do it faster and focus on the part of their work that is the most valuable and rewarding. It’s important to remember that these tools serve to assist, not to replace.
  • Finally, recommendation engines can help you increase customer satisfaction by enabling you to better meet your customers’ needs and expectations thanks to offer personalisation.

 

All the abovementioned business benefits are great, however, the most exciting data use cases are ones which leverage automation. Many repetitive tasks, so far reserved only for humans, can now be done by algorithms.

Employing automation technology in your business can help you see a range of optimisations across your organisation.

  • Faster business scalability. By automating your work processes, you’ll be able to scale your business without having to proportionally increase, train, or retain staff.
  • Higher quality at a fraction of the cost. Algorithms don’t get tired and don’t generate high labour costs, meaning that they can unwaveringly ensure the highest quality of even the most repetitive tasks.
  • Increased customer satisfaction. You’ll be able to increase user satisfaction by enhancing quality, decreasing service time, and personalising your services, all while lowering your overall costs.

As you can see, adopting a data-driven approach can be seen as a type of journey—from leveraging data insights, through to making data-based decisions, all the way to automating work processes.

On this journey, you could start by treating your data professionally and introducing dashboards and insights. But first it’s necessary to build trust in your data—this will enable you to turn insights into decisions and then into actions. And finally, you’ll be able to automate certain actions, allowing you to scale your business faster and at a fraction of the cost.

Summary

Your business may have already embarked on its data journey. As such, it’s important to note that although the journey can proceed as we’ve described above, it’s also possible to take advantage of whichever data solution your business happens to need at a given point in time.

For instance, two of our clients decided to leverage automation technology without having gone through the entire journey—this kind of approach does however require that you have a clear business case and support in the form of both people and strong data sets (often external). To learn more about our clients’ automation solutions, read our case studies: DAERA and Leonard Cheshire.

There are many more strategies and tactics that can help you proceed on your data journey. Our advice would be to take a close look at your business and its challenges to discover how and where data solutions could be applied to optimise your operations and processes.

If you’d like to find out more about how data can help you transform your organisation, download our latest complimentary eBook: “How to Build a Data-Driven Organisation”.

Data Driven Organisation Blog Ebook 416X300
Michał Zgrzywa AI Director

AI Director at Objectivity, experienced manager, software developer at heart. 

See all Michał's posts

Related posts

You might be also interested in

Contact

Start your project with Objectivity

CTA Pattern - Contact - Middle