Housing providers collect a wealth of data about assets, customers, operations and, increasingly, smart devices. It’s well documented that data is proliferating at an alarming rate and no longer sits just on premise but in the cloud as well. Using point solutions to manage and unlock the hidden value in your data only solves part of a bigger problem, and often leads to expensive integration challenges. An end-to-end platform approach is needed to ensure that data is efficiently and accurately ingested into the organisation and consumed to an optimum level, supported by a robust governance framework.
It’s no longer just about business intelligence or analytics. For some organisations, just having some decent analytics is a huge step forward, but in taking those initial steps, try to keep the bigger picture in mind to avoid ‘throw away’ investments down the line.
Capturing, assembling, transforming and validating relevant data sources to ensure completeness, integrity and analytics-ready data are a crucial requirement. The automatic creation of a data warehouse, data lakes and organisation-wide data catalogues are valuable features now offered by some vendors.
More than just visuals
Don’t be satisfied with simple visual analytics either. They might give you some quick wins at first, but you’ll soon hit the buffers when you try to address more sophisticated problems. The ability to draw data from multiple sources from both inside and outside your organisation is essential in order to see the whole story in your data.
You need to be able to dynamically recalculate analytics to the current context and highlight data relationships, including associated and unrelated values across your entire data set. Sometimes even waiting just a few minutes for an answer is not good enough. At the same time, your end-users mustn’t be limited to predefined hierarchies or preconceived notions of how data should be related, otherwise key relationships and insights could be missed.
Not all analytics software is equal…
It’s fair to say that not all analytical tools are created equal, and your end-users should be demanding true insights beyond simple analytics. While there is a certain usefulness in knowing ‘what’ has happened, it’s often more important to be able to ascertain ‘why’ things have happened, and ultimately to be able to predict ‘what will’ happen with appropriate degrees of confidence. Thus, the ability to be able to integrate sophisticated predictive tools, such as ‘R’ and ‘Python’ is an increasing requirement. Augmented intelligence capabilities and conversational analytics make the technologies more accessible to end-users rather than being limited to the data scientists.
It is also important how data and information are delivered to the organisation. Any solution must be able to support the full spectrum of use cases, including self-service visualisation, centrally deployed guided analytics applications and dashboards, embedded analytics, mash-ups through self-service portals (both internal and external) and standard reporting, all within a governed framework that is scalable and offers trust for IT.
How data literate are you?
A key piece in the jigsaw, often overlooked in devising data strategies, is that of data literacy – i.e. the ability of end-users to properly understand what the data is telling them and how to apply that knowledge to their roles. Different end-users may each interpret the same bar chart or other data visualisation in different ways, resulting in completely the wrong action or decision being taken. Low data literacy is holding many organisations and teams back, resulting in stalled digital transformation initiatives.
MIT defines data literacy as the ability to read, work with, analyse and argue with data – it’s a skill like any other, and a skill that empowers all levels of workers to ask the right questions of data, build knowledge, make decisions, and communicate meaning to others.
There are a number of factors preventing data from being infused throughout an organisation. That’s why it’s important to consider the following when building a data-driven culture:
- Tackling resistance from the workforce: Organisations and cultures are built on tradition. Change typically sees resistance because some people are simply stuck in their ways. They want to work the way they’ve always worked and make decisions based on gut feel. Raising awareness among this group that the business is moving to a data-driven culture will be critical to success.
- Finding a data champion: Resistance may also come from the top. That’s why data champions must have a seat at the top table. That person would typically not be someone from within IT (which might seem like the easy default) but from an operational part of the business and conferred with appropriate seniority. They can help business executives better see the importance of data and offer guidance.
- Opening new data sets and the role of governance: Employees are likely to be using new datasets to uncover new ideas and new insights that help drive better decisions. Good data governance becomes absolutely essential. When organisations promote the democratisation of data and self-service analytics, leadership must be responsible for governance. It’s vital to ensure that answers and insight are properly vetted and accurate.
What does a data literate workforce mean for organisations?
- Gain quicker insights because you don’t have to rely on just a few data scientists who can only fulfil so many requests and may not have a good understanding of the business questions you need them to answer; instead, everyone is empowered to get insights on their own.
- Make better decisions because your workforce has been trained to ask the right questions with their data and also feels comfortable bringing data to management to support important decisions, plus the ability to question data with an intelligent data scepticism.
- Be on the front foot because you can quickly make sense of your data in order to adapt to what’s coming and stay ahead of demands.
- Foster employee engagement where your staff feel empowered in the decision-making process and benefit from a work environment that encourages collaboration.
You can’t just assume that your end-users are data literate. A data-literacy education programme needs to be a key component of your data strategy.
Derek Hufton is the business development manager at Catalyst-BI.
