A blog by Camilla Hasler, Partnerships Sales Manager at Profusion
I’ve seen several recent articles and Whitepapers which have criticized the usefulness and relevance of data dashboards for today’s businesses. So in this blog, I aim to share in what way I feel that this criticism may be from those who are less aware that today’s AI-infused, augmented Dashboards offer huge potential with adding analytics to where it is most useful. This is based on my data industry experience earlier and also currently at Profusion. I hope to provide some useful factors for others to consider for the next time they are doing a data analytics review. But most importantly I would like to offer some advice to those looking to create the most optimal dashboards for their business.
The first digital dashboards featured in the Aston Martin Lagonda, in the late 1970s where they replaced the traditional dials. So Dashboards have been around in various parts of our lives for some time. For the past seven years, I have worked with clients in detail with the primary aim of helping these companies and brands to get better and more tangible results with data. Dashboards have been around in the industry come a long way in my view, in the past 5-7 years from when businesses were provided with fairly static and simple dashboards in their data platforms and expected clients to work with those insights.
Now that we have augmented, AI-infused dashboards so that we don’t even need much data experience to interpret the data. The insights can be in the format of a dashboard or within that user-specific workflow for example in Instant Messaging. Now viewers can choose to look at one widget or chart or twelve again by preference and according to their needs as a portable widget in their favorite CRM or social media platform. These Data charts can be available on a mobile device and apps in a dashboard too from any source. These are features are all widely available within the Sisense Embedded analytics software platform.
When Category, eCommerce, and insight teams all have different priorities it does seem hard to believe that the best way to serve and support each team is a templated or preset dashboard. It is worth saying that there was a time that I too believed and accepted the limitation that data tools with preset dashboards were the best analytic offering that could be provided for clients. Thinking that if the data itself was collected robustly from a quality source then it could be transformed & interpreted through manual input into slide decks. Like many, I had accepted and even allowed time and resources to work with raw data or to create, update and review simple dashboards.
I did not know at this time about the potential and ease with which, with expertise Dashboards could be customized. I give this example to show that in any review it helps to have a lot of perspective from those who have wider dashboard and analytics experience in the industry. As Angela Merkel once said: “For me, it is always important that I go through all the possible options for a decision.” But also, that more importantly, it was about a more simple, seamless shift away from working with any individual existing data sets to combining these and then using the power of embedded software to do this within my existing platform. Sometimes the effort for companies to adopt another new platform was adding complexity to an already loaded schedule of cross-platform reviews. It was perhaps a step-change too far, from the data reporting that we all knew and were familiar with.
Here are my top tips for the optimal Dashboards:
1. Consider what data you have and the data you’d like to make more accessible? What formats is this data in? Is this structured or unstructured raw data? What state is this data in, will it need Data Cleaning and modelling?
2. How many people in your company would you like to view data and how many would you like to be able to design and update it. Note this does not have to be only those in IT and technical roles. The right analytics platform will allow more than just technical people to create charts and dashboards.
3. Where does your key analytics workforce spend most of their time, which platform, or messaging apps?
4. What are your overall user groups for the dashboard? Clients or internal colleagues? Are you looking to create a summary dashboard for multiple teams or the exec or other teams? Remember you don’t have to cram all of your insights into one Dashboard.
5. Create a priority for your dashboard creation and build. What are the key business challenges, questions, and gaps in your company’s and team analytics and insight today? This may be from internal or from client feedback. Another way to approach this is where is the time going today in regular reporting. You may need to do a quick survey of how many reports are being run and consider those which take the most time and are mostly used internally. Ultimately what’s the priority?
For more tips and info like that above please reach out to me on LinkedIn and see the www.profusion.com website.
If companies spend time reacting, anticipating, and predicting B2B and B2C client needs, a better way is to support many companies is to create the data dashboards for their specific use cases and questions within broader limits. By doing this we create freedom for companies to choose view by team and role, to then continue after to update and combine their data and dashboards. Data is an ever-evolving mass of information and similarly, a dashboard can be outdated almost as soon as we apply and leverage it.
So, this is where the potential of Real-time dashboard analysis becomes very relevant. Since working in my Partnership role with Sisense I am more aware that there is a need for functionality and data analytics options amongst insight leaders and creators. That this is about empowering clients and enabling end-users to achieve more and take critical decisions to have the functionality to take action right alongside that data dashboard.
It is also worth noting that in any analytics platform review, most companies will want to benchmark options. But certainly, from my perspective knowing the available data analysis options, I can’t think of many reasons why if budget permits, I would want to choose a platform with fewer or more limited analysis views for my organization.
As David Suzuki said: We must reinvent a future free of blinders so that we can choose from real options.