BI and the need for speed

In fact, for extracting maximum value from your data, research shows that speed matters a lot. It’s why two thirds of organisations are investing real-time data solutions to get actionable business intelligence earlier. Meanwhile, half of organisations either currently or plan to use artificial intelligence (AI) to automate the capture of insights that might otherwise be lost. 

Here’s a closer look at the data ‘speed challenge’ - and at how to avoid falling behind. 

Data and decision-making: why time is of the essence

To make informed, timely decisions, you need the right information, at the right time, in the right format - and in front of the right people. Collectively, we call these the 4 ‘R’s. 

There are numerous scenarios in which the need for as-it-happens insight and action is especially important. Here are just a few:

Supply chain management. Particularly in the likes of construction and retail, logjams in the supply chain can translate directly into lost profit. Businesses need to know if delays are happening right at the point of occurrence. This includes the ability to assess the likely impact of those events to determine whether alternative provision needs to be made. 

Inventory management. As with supply chain issues, data relating to your inventory provides a useful early-warning function. If it suddenly appears that sales volume will exceed projections - or if there’s an unexpected drop-off, you need to know about it. An absence of intelligence can lead to a failure to replenish in time to take advantage of an upward spike, or it can lead to a glut of unsold stock. 

Improving the customer experience. Most unhappy customers do not complain; they simply walk away. Sentiment, expectations and preferences can all shift rapidly. Drawing on data from your customer support team, customer apps, CRM system, social media and more, you need the ability to capture and decipher customer behaviour. This helps you understand shifting trends, to quickly remedy service issues and to tweak your offerings and pricing. 

Supporting your latest IoT projects. Microsoft’s research suggests that 94% of businesses will have adopted IoT technology in one form or other by the end of 2020. From risk assessment and automated customer service in insurance, through to detecting and remedying energy leakage in property management, the application of IoT is now mainstream. 

Insights gleaned from connected devices can have tremendous benefit. Not least, they can allow you to proactively troubleshoot product faults, reach out to customers at their precise point of need and roll out hyper-relevant recommendations. To achieve this however, you have to be quick. The data you need may only exist for split seconds, requiring you to capture, process and act upon it instantaneously. 

What are the barriers to rapid insight? 

Getting the 4 Rs right is a big undertaking - and many businesses are falling behind. The problem tends to have three core elements: access, capture and latency. 

The access problem is where people do not have what they need, in a usable format, at their fingertips. As an illustration, one recent survey shows that when staff need data to take action, only 3% have instant access to it. For 60%, getting that data takes hours or days.

The capture issue is where data is generated, but there isn’t the technical capability to harness it. 

Data latency relates to the time it takes for data to travel from one location to another. For many IoT functions for instance, data must be captured, processed and acted upon simultaneously (zero-data latency). In other instances (e.g. rolling budgets and sales analysis), insights are required  - maybe not instantly - but very soon after the data is generated (near-time latency). 

Fast data checklist: are you keeping up?

Every moment of every day, your organisation almost certainly processes a wide variety of data categories for an even wider range of purposes. Your mission is to capture the raw data, reduce latency where appropriate, and to make the data available to the people who matter. Simple in theory, perhaps; but not always so easy in practice. 

To assess whether you are getting it right, think about how far the following statements apply to your organisation… 

1. We have identified the categories of data flowing from and through our business systems. We have the ability to capture what we need. 

2. We have a clear understanding of which data processing tasks demand zero, near-time or some-time latency.  

3. For extremely time-sensitive tasks, we can instantaneously capture data and take the required action automatically.

4. We have the resources to rapidly process complex, unstructured (but potentially valuable) data.

5. For upcoming IoT projects, we have the infrastructure, warehousing and bandwidth in place to handle the increased data volume and processing speed requirements. 

6. We can read the ‘data signals’ and respond rapidly. But at the same time, we have the ability to collect, collate and analyse these signals for analytical purposes such as performance management and forecasting.

7. Our managers can track key performance indicators in near-time. They can also set up real-time alerts to quickly identify anomalies.

8. On matters such as work-in-progress, customer churn and cash flow, managers can request a report and get rapid access to up-to-date figures.   

9. We have the ability to pre-empt customer needs and address business issues, before they escalate into critical problems. 

What next?

For organisations committed to extracting maximum value from their data, MHR Analytics helps them on their way. With best-in-class data analytics and business intelligence solutions, next-gen warehousing and more, we can assist in scaling up and speeding up your capabilities. If it’s time to accelerate the pace of innovation in your organisation, speak to MHR Analytics today.