The death of the dashboard

A few years ago I was talking about the 'death of the report'. Now I wonder if the 'death of the dashboard' is imminent.

We know data strategies and associated governance models are critical to any company, not just in social housing and that a dashboard is the gateway to specific information perhaps, but like reports used to be, it is becoming more and more a repository for someone simply wanting a quick answer. That is not a bad thing, but in itself it does not solve many problems we face. So, reports and dashboards may provide you with an answer or two, and a quick fix, but do they in all honesty give you solutions to a problem, do they identify where problems lie or indeed what the problem is, I don't think so, not in their entirety. They hint, they tease, they sound good don't they: 'Let's look at our dashboard'.

I'm not ganging up on the dashboard, so please don't call me out for 'dashboardism', or 'Anti-dash'. I'm not against them. I just think we can do better, in fact, I know we can do better.

Let me stop talking about dashboards for now. Let's put that one to bed.

So, as we do in DTL Creative, let us now look at the art of the possible within the data space and the ability to solve problems, even the ones you don't know about. Imagine that. Imagine the ability to proactively look at data as an asset you can turn into gold.

There are many ways you can do this. You can, if you really want to, do the following:

Anomaly detection – identifying (typically in real time) a significant anomaly in the data which is suggestive of action. This could be crucial in maintenance, rents, arrears, voids, you name it.

Use Demand and capacity planning – using internal and external data to predict demand and convert to capacity requirements. Think of repairs, think of development, just two immediate areas perhaps. But really think about it....this could apply to so many areas.

Scenario and outcomes predictions - Yes, it's the crystal ball you've always wanted. You really can use data to look at specific outcomes if you do x, instead of y, or do 'this' instead of 'that'.

Pattern recognition – identification of significant patterns in raw data. Think of ASB, think of complaints, think of any area as a landlord where you can find patterns and then do something about it.

Predictive asset maintenance – predicting when an asset will fail or require maintenance is simpler than you may think.

Prescriptive modelling/action – identification of optimal system inputs to generate desired outcomes, applied again to such areas as repairs could bring real improvements.

Causal analysis – recognition of cause and effect and correlation relationships between entities or events, could be used in neighbourhood management, ASB, arrears and so on. If only you knew what was causing something, imagine what you could do with that information.

Data structuring – conversion of unstructured and semi-structured data (e.g. paper; images, audio; legacy spreadsheets) to structured and usable data through techniques such as Natural Language Processing (NLP) and Computer Vision. This may well sound a bit too technical, but it's not rocket science, well it is science and engineering, it is data science, and it is data engineering.

These are just some techniques you can use to bring value to your data proposition.

The area of data science and engineering is so fundamental in you as a landlord being able to:

1. Deliver more efficiency and more agility through data.
2. Unlocking the value of the data in your housing systems and applications.
3. Make more informed and calculated decisions based on insight and information.
4. Do things faster, easier and costing less. Really!

Now, admit it, you want to know more about the above, and how you as a landlord can drive efficiency and agility, to bring answers and solutions to problems you didn't even know you had, to provide more aligned and effective services to your tenants. And all this is at your fingertips. Yes, you have the raw data, so let's use it. Let's turn it into gold.