Why your business intelligence implementation needs workflows

This year I have worked with my customers on several business intelligence (BI) projects, and from what I have seen, the key to making these systems effective for the business is to go further than they allow on their own

Business intelligence systems are excellent at presenting information in a way that lets the user make informed decisions, but you unlock far more business value by making the data actionable, allowing the user to kick off business processes based on the information.  This turns business intelligence from a dashboard into a control panel for the business.

It makes sense to combine integration and business intelligence tools, indeed they already are combined in order to extract information from the multiple data sources that need to be analysed.  Today’s business intelligence tools are quite capable of collecting and even cleansing data in order to provide the user with high quality data to analyse.  However, the true value of business intelligence is not in data collection but actionability: today business intelligence means dashboards where users can slice and dice information, but what can they do with it once they have made a decision?

Decision-making cycles

Today’s businesses need to be ever more agile, ready and able to respond to market opportunities as they appear.  Just think about the effect a warm weekend in the UK has on barbeque sales, or the number of people who take up baking after watching popular TV shows.  This has always been the case, but as a single social media hashtag can cause immediate effects, it’s becoming more urgent.  It’s also true in the business world, where this year emerging cybersecurity threats such as Heartbleed required instant responses.

What we are trying to do with business intelligence tools is to accelerate the decision-making cycle, which is to say how long it takes you to respond to a change.  It’s sometimes referred to as the “OODA loop”, an initialisation of the components:

Observation: what has happened?
Orientation: what does this mean for me?
Decision: what should I do about it?
Action: completing a action taken

Business intelligence tools accelerate the “observation” phase of the cycle, and I have previously argued that the real-time capabilities of Big Data also help with “orientation”.  I believe that it is possible to use process-based integration to create workflows that can accelerate both the “decision” and “action” parts of the cycle.

Over the last few months I’ve worked with several customers implementing this form of actionable business intelligence, and here are some of the outcomes I’ve seen.

One customer builds underground tunnelling equipment for large projects.  The precision manufacturing of many parts often requires engineers to manually fit them which resulted in unpredictable timeframes, and expensive project delays.  Breaking the assembly process into multiple stages and feeding each into the business intelligence tool allows the status of each operation to be monitored separately and identify where actions had to be taken before delays affected project plans.  Making the business intelligence output actionable allowed the customer to improve the efficiency of maintaining their equipment: they were able to place orders for parts quickly, schedule the availability of engineers on site andbuild these activities into project plans.

My customers

A provider of bundle solutions for household broadband, phone and TV services needed to be able to rapidly identify and respond to any network problems, both in delivery and security. Both the customer’s network monitoring and customer services departments received the business intelligence tool, allowing the provider to gain a better view of current activities.  They use the information to inform decision-making and prioritisation; and when a security breach or network outage is discovered they can immediately assign security professionals or technical resources to fix the problem.  The actionable information also makes it easier to follow up and stay in touch with their clients to ensure continuous service delivery.

A hospital looking to gain visibility on utilisation of beds and treatment scheduling found actionability useful.  They were trying to reduce waiting times and optimise resource use, and to be able to make use of data currently scattered across multiple systems (operation planning, medical journals, administrative systems).  The integrated system is used to track patient history and information in order to improve patient care; and for resource planning by assessing actual versus planned utilisation of beds and resources.  Making their business intelligence actionable allows them to schedule cleaning times to make best use of theatres, notify staff of schedule changes and coordinate effectively between departments.

The final customer supplies raw materials to heavy industries, and needed to gain a clear view of activities across large warehouses, transportation and their many, frequent transactions in order to control material flows.  The fast business cycles involving many customers meant that management was only able to achieve a rough, “finger in the air” view of what was actually happening, but use of a business intelligence tool allowed them to retrieve and display information to make informed decisions.  The company can now track profitability of multiple business units, and is able to better control the materials flow through its warehouses and transportation.  In particular, providing actionable business intelligence dashboards allowed them to improve use of both their own and their clients’ MRP (Manufacturing Resource Program) and ERP software, and warehouse planning with Agilisys.

Everyone understands the value of dashboards, but the next stage is to connect them into decision support systems.  We need to take a strategic view of the entire enterprise system in order to bring together data sources, business intelligence tools, and integrated workflows to create a more automated, agile business.

This post appeared first on David Akka Blog.

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