Top Tips for Creating a Digital Transformation Strategy that Works
Digital transformation is, without a doubt, one of the leading challenges facing the business sector today, where a business that adapts positively and proactively to...
Your data strategy should be driven by your overall business strategy. Once your data is in order, make sure this data matches the objectives of your organisation, your key performance indicators (KPIs) and can be viewed in a consumable format.
This article covers the benefits of becoming a data-led organisation and 10 steps to deployment.
“Data-driven decisions are the antidote to basing your decisions on ‘gut instinct’.”
On any given workday, business leaders are faced with an ongoing and billowing stream of data and information. Every day, they and their teams are required to make hundreds to thousands of business decisions.
Most reporting only has a backward-looking view using data from what’s already happened, when actually, every business wants to be forward-looking.
Often these decisions are made based on previous experiences, ‘business as usual’, or staying in your comfort zone instead of blending new and existing data and insights. The challenge then is: How can executives decipher the meaningful information from the clutter? How can they ensure that they make an impact for the business against the flush of information washing over them? How can they become catalysts of change? Forward looking views will allow for course-correction.
Organisations aren’t sweating their data assets, they’re using poor quality data, not setting the right KPIs and there’s a heavy reliance on I.T. They don’t know what they want to see in terms of data, but it can all be within their grasp. Finding the right KPIs should start with your business goals. In order to help get the right KPIs, companies should map out their strategy, and then develop the key performance questions they need to have an answer to.
Before you invest in technology to help with business intelligence reporting, it is essential that you invest time upfront on really understanding what your user’s data needs are, and how they are currently carrying out their job. Then you can assess the systems they already have access to, and how beneficial they are to them.
Determine who your business intelligence (BI) users are before deciding on the solution to deliver your business intelligence.
You could consider creating user profiles/personas for each type of user in your organisation. Upon doing this step you will be able to identify common themes and requirements between cross-sections of your users, and in turn this will enable you to group them.
Categorise your user groups.
Time and time again we see the same generic reports and dashboards. In order to achieve adoption of BI, categorise your user groups, then design dashboards and reports per group.
The Discovery phase is important. Once you know who your users are, break the discovery phase down into phases:
|1||Identify user groups|
|2||What type of experience do your user groups need to have with your data in order to gain the most value?|
|3||What platforms/devices will they need? This may change throughout their working day, so must be seamless from device to device.|
|4||Map your user groups to your data sources. This will help you identify the most efficient data structure, in terms of the design of your future data warehouse.|
|1.||KNOW YOUR WHY
Every change must start with why.
Invest in creating a strategy.
Change happens with Leaders.
This is a Business Transformation.
|5.||PEOPLE, PROCESSES, THEN TECHNOLOGY
Stay on track with what the business requires.
|6.||MAP OUT THE BI USER JOURNEY
Nobody is the same, that’s what makes the world so different.
|7.||FIT FOR PURPOSE TRAINING
Classroom training isn’t for everybody.
This is a business led initiative, but you must involve I.T.
It’s all about adoption.
Monitor and adjust.
The objective of any BI project is to create a solution that can not only deliver a ‘single version of the truth’ that can be interrogated, but also the most efficient method to do this so that the data can be trusted and remains relevant in a fast-moving environment.
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