4 Components of an Effective Businesses Intelligence Data Strategy

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    Written by Simon Porri

    Companies of all shapes and sizes are looking for ways to not just collect and analyse data, but also turn it into a business intelligence data strategy that helps make the right business decisions in a time of disruption and rapid changes.

    An effective business intelligence data strategy relies on: 

    1. Effective access to digital records
    2. Automated updates and analysis
    3. Integrated communication tools
    4. A single source of truth

    Here, we are going to explain how to get the most out of your data and update your business intelligence strategy. Fundamentally, there has never been a more important time to get this right. Intelligent use of data is your key to making the right decisions within a rapidly changing and highly competitive economy. Identify strategies to improve business efficiency, creatively adapt to new opportunities, and shore up risk without limiting your potential.  

    Creating an effective business intelligence data strategy is a critically important topic to us. We built our own business intelligence, Loop, specifically to simplify business intelligence data analysis. To a large degree, this article is about walking you through what we deliver to customers. But the core fundamentals remain the same no matter what business intelligence software you use. Let’s get started.

    Component #1: Digitise and centralise data — including historical data

    Businesses worldwide are taking big steps towards digitalisation. But digitising data isn’t enough. You also need to centralise access and analytics in order to prevent data silos. You need to make sure that all of your existing data is accessible by your business intelligence system, otherwise you may be missing out on key insights and patterns that could help drive effective decision making.  

    Why this is critical

    Businesses just getting started with business intelligence often have a mix of paper and digital records. The former can be hard to access or lost, while the latter are stored in different sources and formats. That’s why they need completely digital records as well as a BI tool that can pull business information from any number of third-party sources.

    Imagine different organisational functions or franchises storing redundant or inconsistent data — the resulting cost can be enormous. What you want is that ability for anyone to log on to a single tool and get a complete overview of your business data in one place. 

    Strategies to help

    A proper centralisation strategy generally follows these steps:

    1. Determine your goals, tools, access protocols, and security measures
    2. Digitise paper data
    3. Standardise digital records
    4. Migrate data from multiple sources to one database
    5. Issue permission levels
    6. Maintain and control the database

    For businesses struggling with getting started, Loop can deliver this as a managed service — we will work with businesses as a strategic partner to ensure beneficial outcomes. Ultimately, this creates a single source of truth, ensuring data is correct, and is the critical first step to effectively accessing data.

    Component #2: Automate the capture of future data

    Data requires maintenance, and updating data is part of that. Out-of-date data, like obsolete customer addresses or old versions of documents, can lead to costly errors and misinformed decisions. However, updating records is often a time-hungry task. 

    Why this is critical

    Once you’ve digitised all of your data, you don’t want to be endlessly encumbered by manual re-entry and updating. What’s more, manual data entry can cause errors, and is simply not a scalable solution. It’s critical that you automate and simplify workflows in order to free time to use data rather than just catalogue it.

    Strategies to help

    You need to prioritise automation from a process standpoint and acquire the technical capability for it. Your BI tool must be able to automate the processes of capturing and updating data.

    All data in Loop is automated on setup, even when it comes from a multitude of sources — including third-party providers (with permission) i.e. audits or customer satisfaction survey scores (e.g. NPS scores and CSAT scores). The more automation you can build into the system the better, and your business intelligence tool should help you do this, rather than make your life harder. 

    Component #3: Ensure all data is captured at a granular level

    While larger data volumes are important for uncovering patterns, you also need to look at data at its smallest, most detailed level. The availability of granular data reveals exactly what issues are lurking amidst things like customer behaviour or the performance of media creatives, and makes predictive analytics more accurate. It also reduces error by ensuring that your calculations are built on unprocessed data feeds. But without the right tools, gathering and analysing granular data can be very challenging.

    Why this is critical

    Capturing data at its most granular level allows all aggregations and calculations based on that data to be systematized. This removes manual workloads along with the risk of error, thus delivering consistency in calculations and reporting.

    If secondary data (aggregated or partially analysed data) forms the basis of further calculations, any mistakes in those original manual calculations will impact outcomes. Automation prevents this and frees up the time to focus on optimising performance.

    Strategies to help

    You need a process in place (right from the start) that prioritises granular data capture. Also, the business intelligence tool you choose should be compatible with enough third-party sources that you are able to pull granular data directly from the source.

    Loop is a good fit from both a process and a technical standpoint. For instance, you can send surveys to assess compliance with standards throughout all your locations. You can also look at data of on-site visits to manage them efficiently.

    Component #4: Have a plan and the tools needed for action

    Data is only valuable if you can use it to drive actions that ultimately improve your bottom line. So your BI data strategy must incorporate tools for action, and you need to foster a business culture that looks to data sets and BI tools to make strategic and tactical decisions. This is what separates Loop from other BI systems: it’s focused on taking data-driven action.

    Why this is critical

    It’s easy to get lost while trying to enact the necessary changes. Before creating sound and timely actions plans, you need a tool that allows you to:

    • Set Key Performance Indicators (KPIs) that are aligned with your business goals and measure them with relevant data — a common hurdle is the overwhelming amount of data that leads to tracking too many or the wrong KPIs.
    • Visualise data in a clear yet comprehensive manner. You need to convey and compare performance in key business areas in a way anyone can understand. Balanced scorecards are particularly effective for that.
    • Easily communicate information across your organisation or network. This ensures everyone takes the right actions based on strategic decision making.
    • Automate tedious manual tasks to save the time needed to devise and execute action plans.

    Strategies to help

    Your BI tool must go beyond data analytics – it should make taking action based on accurate data easy. Below are some of the features included in Loop that we built specifically to help you take actions based on the data you’ve collected:

    • Dashboards: You can set and display KPIs to monitor the performance of your business. Loop analyses data to show you the metrics that matter.
    • Action planning: Create actions, set targets against KPIs, share these actions, track progress, and measure impact.
    • Balanced scorecard: This BI framework displays operational and experiential performances with KPIs to highlight weaknesses and opportunities for improvement.
    • Usage reports: Keep an eye on the big picture by monitoring how Loop is used across your organisation.

    Suggested reading: If you want to learn more about the difference between data and action, check out our blog — What Are Actionable Insights? 

    Data’s value hinges on affecting actions

    All data must be collected and used with the end goal in mind: reaching profitable outcomes like satisfying customers and reducing costs. When you have easy access to accurate data, you can uncover actionable insights and close the gap between data and outcomes via action plans.

    To do that, you need to:

    • Digitise and centralise data
    • Automate data capture and updates
    • Capture data at a granular level
    • Create action plans with the right BI tools

    Companies armed with a strong business intelligence data strategy are better equipped to face the rapid changes in the current world. Loop will help you implement your strategy to make the most out of your data and thrive in the future.

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