Enhance your Competitiveness with the Digital and IoT Enterprise.

Big-Data, IoT and IoE initiatives are mostly about analytics and real-time decision enablement  

According to Gartner 72% of companies have one form or another of a Big-data Initiative underway. According to the same source fewer than 30% of these initiatives would deliver any true business benefits or meet business expectations. So while investments are high the BVA (Business Value Attainment) factor score continues to remain low. Unless you think a ROI of under 30% is acceptable. This is concern 1 for most companies commencing their digital journey.

We started with an IoT events way back at Palo Alto, CA back in  Nov 2014 and realized that we were facing an audience that queried us on whether what we presented was just ‘smoke and mirrors’. We followed these clarifications with another event in April 2015 with a series of IoT demo’s and suddenly the competitive positioning opportunities started to click into place when most attendees realized that IoT and IoE were a real paradigm shift happening all around. On April 6^th,2016 we help our ‘Road-2-HANA- The digital Enterprise’ event in New York which this was a resounding success. By the way you can still register and get access to the post event presentation slides and videos.  

In most ways, Internet of Things (IoT) is mainly about collecting enterprise digital dust from currently connected, semi-connected and dumb data generators. Only when we start to collect this digital dust is when we realize that analytics are like any other analytics. In this digital enterprise journey the first step is digitization, the second is analyzing the history of these data generators and the third is extracting decision capable analytics via patterns and algorithms from this digital dust. The Big-Data, IoT, IoE analytics mostly conform to the same rules and design decisions as we have been using in traditional  business intelligence (BI) and advanced analytics. Even so, the IoT is creating unparalleled information management and analytics challenges. This is concern 2 on route to establishing our digital enterprise- the fact that Gartner reported in 2012 that current BI initiatives are delivering less than 40% business benefits from thei BI projects. My validation, and interpretation, of this statement is by validating whether this statement is true of false. ‘Move than 60% of the reports in your BI production system are not being used, or will never be used, by your business users’. I have been asking this question to BI managers since 2011 and in every honest reply I slowly get a ‘..probably more than that.’

During our event in New York we briefly touched on the evolutionary steps for a current enterprise to the launch itself into a digital enterprise. We also discussed the difference between IoT, which is like a digital hub and step 1, and IoE which is the end goal of digital connectivity and digital dust generation.

Why is IoE and IoE important?

According to Garner by 2020 50% of major competitive enterprises will have some element of IoT installed and will be capturing essential predictive data?  The message is CLEAR – ‘DISRUPT or be DIRUPTED’ the choice now is yours.

According to our research by 2020 30% of companies will change their business models, i.e. from being sellers of air compressors to simply selling Air-as-a-Service by leveraging predictive maintenance and guaranteeing constant air supply to users without any incumbency of breakdown or old equipment.

In order to meet these requirements business stakeholders will need to firstly define the business needs and the business cases. Start with the business needs so you don’t get lost in the data deluge.  Once you have identified that, we do it with a business focused ‘Design Thinking’ workshop that extracts unique business needs that are otherwise impossible to spot, identify or extract. This becomes the baseline for the digital transformation. This is where we sieve the coal from the diamonds. This is but the beginning.

We simultaneously re-tool our users from Reports to Analytics and then from Analytics to Informatics. We need to retool them from reading reports to real-time decision enhancement. We also need to make them aware of Analytics, Predictive Analytics and Prescriptive analytics which is already taking out all the human errors and replacing them with pattern based algorithms.

Concern 3: We can no longer afford to create technocratic reports and analytics with a 30% ROI. With such large data volumes, we need to keep our data engines surgically clean and effective for real-time decisions. We can no longer apply the same rules, the same architecture and decisions that have go us here. We need to change our partners, architecture, Infrastructure, methodology to optimize our digital experience.

 So what makes the digital and IoT data different?

As our data volumes, velocity, variety and veracity increases algebraically we need to fine-tune our analytics engines like a formula-1 racing car. I published this in a book in 2010 ‘BI Valuenomics’ see end of this post for details, which is more relevant today than when it was published 4 years ago.

The changing lens of 360° Decision Enablement

Attribute	Legacy	Current - Digital
Data Sources	Inside the Enterprise Firewall	Upstream, Downstream and Midstream
Data Volume	Low	Very High
Data Extraction	Periodic	Streaming
Data Sources	Few System with static Data	Data in Motion, streaming from sensors
Extraction	Periodic ETL	ELT, store, blend and manage massive data
Value Chain	Midstream	Downstream and Upstream
Data Type	90% Structured enterprise	Growing unstructured streaming data
Information	Reports & Dashboards	Real-time Decision metrics and alerts
Complexity	Low	Medium to very high
Analytics	Centralized	Distributed to the edge
Transformations	Manual and static	Pattern based automatic algorithm’s
Point of transform	ETL to ELT (transform at DW)	TEL (Transform at Source) then extract
Communication	One way to DW	Bi-Directional in Real-Time

What got us here will not get you there

Remember your current architecture and design capabilities are running at 30% efficiency, i.e. 70% of your data is either redundant or worse dead data. So continue with your current paradigms and  your decision system will enter a dark place we don’t want to even discuss here. So Plan your work and only then work your plan.

What will your Digital Enterprise require.

Better Infrastructure Partners: Your legacy partners have been experts in the midstream enterprise requirements, i.e. HW, servers and storage. Your future needs are going to be driven by Big-Data, which resides at the edge, by IoT which requires networking and communications, by IoE which will require connected products and then interconnected devices, and most important of all a dynamic and scalable architecture that does not lock you into long term boxed contracts- like an appliance for SAP HANA.

Better Connectivity: According to Michael Porter the connected enterprise is changing the very definition of an industry and thus your enterprise. So connections, sensors and networking are going to be the keys to success over the next decade.

Better Real-Time Decisions: It will not matter how many millions of dollars you spend. It will not matter how much technology one buys. It does not matter how big-4 your partners are. It will not matter if your project delivers 6,000 or 8,000 reports or 3,000 ODS’s and Cubes. The only thing that matters is how much the end results impacts your day-to-day operations and the enterprise decision capabilities.

What your need to plan for

More Business Participation: I stated this in 2010 and I state it today. Any Si partner that requires your business stakeholders to be kept outside the doors of your Big-Data, Cloud, IoT, BI or SAP HANA projects must be shown the door very rapidly. The only path to success is to get business involved in a ‘design Thinking’ workshop before you start your project.

More Data: Your data is not only going to be high volume, velocity, variety and voracity but it will get more and more unstructured. Your designers will need to play with non-repetitive data streams tht will come streaming and the challenge is going to be where to keep your data in motion.

 More Complexity: Digital Enterprises will no longer collect their data from enterprise, structured applications but from across the planet in very strange and complex formats that will be generated in devices, pass through controlled clouds and systems, zip through servers, filtered via smart routers at the closest point fo data generators and then placed in low cost data lakes. This data will then need to be enterprise harmonized and then merged with structured data that users are familiar with. We need to take a leap from analytics to informatics very rapidly with a high focus on true business benefits.

More Automation: With data generators that produce very large streaming bits of data the only way to do all the above is to identify patterns and the deploy algorithms to automate the data flow and transformation processes as close to the source as possible. The IoT informatics system will be as strong as its weakest link, where a stitch in time will always save nine.

More Secure: This one should actually sit at the top of these topics but it is hard to start with security if one does not comprehend the width and depth of the digital data flows from the edge. As the enterprise doors open to let in data from the edge it will also leave the same doors open for hackers and undesirables to come in via the edge streams right into the heart of enterprise systems. So before you start your Big-Data, IoT, Cloud or SAP HANA initiative start with security. Start with a universal security fabric that runs from one edge to the other. Remember the cardinal rule the undesirables know the edge devices are the least secure so they tend to reside there to gain entry into your enterprise jewels.

…oo ––ššÅÆ››—— oo…