Actionable insights are those that make managers and workers 'curious' and cause them to act. The big data revolution is giving organizations many more reasons to exploit data so they can improve customer experience, personalize offers, improve sales engagement methods, optimize processes and surface BLUE OCEAN opportunities. Even your existing data that's locked away in back-office systems can become extremely value when combined with other data to answer new questions. But what PROCESS do you need to harvest actionable insights and act on them to accelerate the pace of innovation in your business?
In this article I've summarized the obvious 5-steps to turning sleepy data into (first) actionable insights and (then ultimately) better processes using big data cloud computing and operational analytics technology. Then I've explained the 2-step process (yep just two steps) that Encanvas makes possible. While the example below is based on the capabilities of the Encanvas platform because we're familiar with it at NDMC there are other technologies from Tibco, IBM and Oracle that you could also consider to achieve the same outcome (though this is probably an 'IT' project if you do).
The reason we developed and continue to use Encanvas at NDMC is because it produces the fastest time to value by reducing the number of steps in the Accelerated Business Innovation process - and it deskills the activity of process innovation so you don't need to be an IT expert or programmer to implement it.
A typical 5-step innovation life-cycle process using a mix of enabling tools is:
1. Capture Data - 2. Hoard Data - 3. Harvest/ETL - 4. Analyze - 5. Act
This can be a long-winded and technically challenging process: It requires a different bit of software for every stage, and this results in large IT teams, expert skills and slow time-to-value projects.
Why 'Acting' on actionable insights is like exploring for oil
The accelerated business innovation process is modeled around oil exploration where you first make sure you've hit oil before you start to build infrastructure. This means that when actionable insights surface a better way of working, the solution is to create a situational application (at little or no cost) to validate the process change. If the new process works better and provides incremental value then it is adopted, if not, it is discarded. That takes a new approach to IT and new tools. The most challenging part of adopting an accelerated business innovation process using legacy enterprise software is therefore the 'ACT' bit. Adapting legacy platforms like Oracle, SAP and Microsoft Dynamics is more akin to turning an oil tanker - really difficult and expensive: It requires IT people with deep skills. That's why we use Encanvas to serve the long-tail of situational applications that are used to 'explore' value and then adopt those applications that prove valuable as a layer that sits above the fragile 'heavy-lifting' enterprise software that most businesses operate today.
1. Assimilate data
Data assimilation describes the task of bringing together data to a level of consistency and completeness that makes it useful. The term means more than simply
harvesting data - because anyone who has tried to bring data together from different sources (even using a spreadsheet) knows how time consuming and painful it can be to extract, organize and structure data. Fortunately, tooling is available nowadays to automate many of these very manual tasks.
Many people assumption - probably due to the norms of behavior encouraged by decades of data warehousing - that it's necessary to
hoard data and organize it before you can start to lever insights from it. Nope. Today, the data harvesting, data source integration, data augmentatation and normalization tools are so powerful that most operational analytics systems can 'get at the data' wherever it is and exploit it without having to first HOARD the data in some great big massive repository that you have to pay for. (That said, if you do want to hoard data, technologies like Hadoop have made the task of hoarding data of different forms immeasurably less expensive and more scalable.)
Encanvas, and technologies like it incorporate a full range of data connection and
ETL tools that obviate the need to code or use lots of APIs and middle-ware tools in order to harvest data. It supports data integration with CCTV, security databases, hardware, sensors and telematics. Whats more, it enables situational applications designers to exploit structured data (like relational databases, web services, CSV files etc.) and unstructured data (such as PDF documents). Their Information Flow Designer application gives applications designers the means to formalize data gathering workflows from data sources, transform, cleanse and normalize data - and then expose it for operational analytics applications like Encanvas Create Design Studio to exploit.
One thing we realized at NDMC a decade ago is that authoring exploratory (situational) applications to source actionable insights requires designers to play-around with data, forms and logic tools - all the toys needed to create exploratory apps in the same integrated design environment. That means you need the data sources to play around with too. Encanvas allows us to try things out, get things wrong and work with stakeholders until we get a result. Assimilation of data is tricky, sometime painful and rarely straight-forward!
2. Create and Deploy Situational Applications
Sourcing actionable insights normally means connecting to many different data silos and exposing the data held within them. The 'clever bit' that technology can help you with is to bring data together in new ways, to then formalize business processes to act on it.
This 'iteration' of the enterprise computing environment requires to perpetual creation of
situational applications that serve individuals or small communities of users that traditional IT can't service because this long-tail of demand is simply too long to be addressed by technology platforms that need coding - and users have such a diversity of requirements for tooling. While there is a natural instinct to employ existing tool-kits like IBM WebSphere, Microsoft SharePoint or applications platforms like Force.com, art NDMC we foudn this to be a costly approach because it requires large IT teams and the tooling is limited by the capabilities of the platform. None of these enterprise platforms were engineered for the purpose of authoring situational applications and so IT people find themselves knee-deep in APIs, forms and database programming projects and third party data analytics and data source connectivity tools.
Using built for purpose environments like Encanvas, situational applications are created in a codeless integrated design environment. We use the same environment to author operational analytics as we do actionable applications - and very often an exploratory application for operational analytics can be progressively extended to become a key part of the enterprise operating environment.
In the normal course of an accelerated business innovation project, stakeholders will start by creating
operational analytics applications to analyze their data. Then they will create applications to
ACT on the results of the 'data analysis' exercise.
When data does not exist, new applications are authored (for desktop, tablet or mobile devices) to
capture data. When authoring such applications it make sense to control the quality of data input wherever possible by adopting the use of drop-down choice fields, radar buttons,check boxes and check-lists. When working with Encanvas, even applications used to capture data can be 'situational'. Very often these applications are eventually absorbed by 'platform' systems like Microsoft SharePoint, Oracle and SAP.
How long does it take to execute an accelerated business innovation project from 'concept to completion?
After a decade of examples we know that the answer depends on a number of factors:
1. The size of a project - Smaller projects (i.e. Something akin to displacing the use of spreadsheets for analysis of audit and accounting processes) can be actioned within a day, sometimes two. Large projects take significantly longer. When we've employed accelerated business innovation to upgrade a regional transport system, enhance an eLearning system, install federated risk or compliance across a business - that sort of thing - it normally takes around 6-weeks to get through the situational applications phase and move on to User Testing or 'embedding' the technology deployment into the enterprise platform. While 6-weeks is a long time it is nothing compared to traditional IT projects that span many months, sometimes years.
2. The change methodology - We are supporting a change process and so inevitably HOW you run a project will impact on the pace of achieving outcomes. An NDMC we've created a Computer Aided Applications Development methodology to support accelerated business innovation projects. This combines the 'good thinking' found in Outcome Driven Innovation (ODI) and Blue Ocean strategy mapping in addition to a few other methods that are unique to our approach.
3. The tools - If you're using a codeless and complete situational applications design environment like Encanvas Design Studio then 90% of the programming, testing and tuning overhead authoring process is normally removed from the exercise - and stakeholders can contribute to workshop-based developments. This speeds up the innovation process because project leads can achieve an outcome during the course of a 3 or 4-hour session rather than just creating 'a list of things to complete'. If you are required to use tool-kits like Microsoft SharePoint THEN YOU CAN still achieve great results but it does mean you will need a dozen more IT people to support the process.
I hope you found this article on accelerated business innovation interesting. Do let me know of your own experiences.
Ian.
