The
word “Force Multiplier,” is used by the military usage, refers to any process
that acts like an accelerator catalyst when combined with another process
enabler. Force multiplier effect is when the joint impact becomes greater than either of the two processes ,or
their individual additions, on the end result.
So
what processes would work as force multipliers in an IoT and Big Data world? Based
on our experience in identifying and often creating new products for the
commercial and IoE world we believe that great products need three legs to
become truly effective.
1. The Human connection: At the end of everything
the final interpretations should not be representative of how complex the data
science was but how easily the human mind can interpret, and take necessary
decision, from the information. Just like in traditional BI, when data is left
to the technocrats we get a lot of reports and interpretations but not
necessarily business transformational analytics. If you don’t plan for
attaining business value then don’t expect to reach that destination by
chance. Without the human connection factor
we can have solutions that only the scientists can understand, rather than
answers that make all the underlying data invisible. Due consideration must be
made as a user at a box manufacturer thinks very differently from a CPG user
from an Army major or a CERN scientist. Never forget the human factor or what
we refer to as Business Value Attainment. Success of any new technology
initiative must be measured only by how much it optimizes the day-to-day tasks
of the business consumer accomplish their tasks more efficiently
2. Invisible Data Science: Data Science is the
ability to use scientific principles with statistical algorithms by identifying
patterns in very large volumes of data to identify previously unknown signals
in a new and real-time manner. However, the big question in BI, SAP BW, BW on HANA
and Big Data is how much of this complexity needs to be exposed to the
consumer. The best deliverables are where the underlying data and the science
becomes invisible and only the decision relevant information, alerts,
predictions or prescriptions remain visible. Great analytics do not reek of
complexities, data or algorithms but only of simple visualizations that enhance
decisions. Simplicity is a not a technology solution but a human neural pathway
nuance that gets activated by the right stimulus. Data
Science has evolved quite a bit in the evolving definition on the role of data
scientist. Initially in discovery phase it was very cold and technocratic. It
then evolved by leveraging people from statistics and a background of working
with very large data sets. It has now come to a point where simply producing
interesting technical graphs is no longer the desired goal. The human factor is
becoming more and more important. The new sauce is the ability to understand
business benefits, human neural pathways, human behavioral science and user
needs and then to deliver analytics where the underlying technical algorithms
and data science becomes invisible. We are cross training our data scientists
from being cold statisticians to warm behavioral science, business benefit and
the human factor experts too.
3. The Technology: the foundation of all
this is the technical capability of available options that can perform the
tasks in accordance to predictable timeframes. As
a baseline there is a need to have a minimum technology platform and
infrastructure to meet some of the new challenges as a lowest prequalification
for playing the big data game. For SAP customers it could be HANA, Hadoop,
Horton Works/ Cloudera/ Sparks and Business Objects.
While there is a lot of ongoing discussion of the
business benefits and the operational side of IoE and Big-Data, one thing is
becoming very clear ‘..in the near future enterprises should be less concerned
about the sheer volume of of IoE device data, and more concerned about making
it usable by different layers of consumers and administrators. For example Duke
Energy is already thinking of the IoE competitive differentiator by enabling
buildings, support vehicles, people, power plants and smart meters integrated
into their operational analytics and management informatics. The problem here
is no the data but in making it relevant for decision enhancement.
Based on our lessons learned from the BI projects in the
last two to three decades we need to firstly level the playing field by
accepting the Gartners 2003 and 2012 BI reports that empirically reported that
50% and then only 30% of BI projects will meet business expectations. Anyone
having read my papers is probably familiar, or even bored, with these Gartner
stats – but the major question is what have each of us done about it and how do
we plan to mitigate this risk as our data volumes explode in the very near
future. Do we still want to work with the same partners, their experts, their
resources and their methodologies that have got us to our current state where
according to Gartner ‘more than 70% of
the reports in your current BI production environment are not being used, or
will never be used, by your business users’. Do you plan to replicate this
reality in your new big-data and HANA platform?
Here are three
real-life examples that we would like to share with you:
Business Scenario 1: Using IoE for higher customer
experience and lower operational risk in the Hospitality sector. PrideVel is already a major provider of
hospitality application for hotels and hospitals with applications and
solutions for guest experience solutions. With the advent of the IoE connected
device capabilities we are now looking at adding networked devices with
capabilities of temp and humidity alerts from rooms, boilers, chillers, fire
sensors, smoke sensors, humidity sensors, across hundreds of establishments and
buildings in real-time. These centralized real-time streams are managed by a
central command center that have a holistic view of a group of enterprise
buildings, or hotels across a region, or a residential complex of high-rise
buildings. These new IoT options for the hospitality sector provide real time
alerts to critical risks like fire, leakages, unauthorized intrusion with a
real-time visibility of mitigation assets in the proximity of the risk.
Business Scenario 2: Using IoE for higher customer
experience and lower operational risk in the Utility sector. Three factors are making huge
difference in the utilities segment. The first is Smart Meters and all the data
they produce that can be mined, filtered and shared with consumers for changing
their usage patterns. The second is the ability of a home or an alternative
provider becoming a provider and consumer of electricity. Homes, institutions
and providers by installing solar panels, or other forms of generation
capacity, on their property. The third is aging gas pipelines that need to be
professionally monitored, tracked and replaced and scientifically monitored in
order to avoid a gas explosion in a residential area like it happened in the
San Bruno fire that gutted many residential homes and resulted in more deaths. There
are solutions available for each of the three scenarios today.
Business Scenario 3: Weaving IoE into the strategic
selection of partners, methodology and deliverables applicable to general
segments. In the
strategic context almost every customer investing into SAP HANA has a high
probability of using external data sources sometime in the near future.
External here refers to the upstream and downstream value chain partners who
have the potential to produce data that can impact decision efficiencies. This
in a world where currently over 90% of enterprise analytics are currently
conducted only on the midstream data, i.e. processes existing within the
enterprise firewalls. Pridevel has created an asset base of SAP and SAP HANA
strategic workshops combined with automated recalibration products. On one side
our workshops provide executive checklists for strategic decisions including
critical questions to ask for partner selection and at different phases of the
HANA deployment initiatives. On the other we have a sleuth of automated
products that meet our IQDCT (Increase Quality, Decrease Cost and Time)
philosophy. By weaving strategic ‘business benefit’ considerations into the
planning phase we have consistently saved companies millions of dollars in
their HANA installation or migration plans.
Why is the human factor in HANA
deployments important?
It has more
than been validated that in most companies business actually funds most
IT projects. Thus, business is the prime customer for new initiative and
most of the IT deliverables like SAP HANA. It is business that is the judge and
jury of what IT finally delivers. If business users do not like what they
receive the project becomes a disaster zone rather rapidly.
It is also currently prevalent to find that in
many companies the following scenario: IT wants to deploy SAP HANA but business
is stalling the decision with a ‘Show me the business benefit first’. Inn some
cases IT has already deployed the technical solution but business is
floundering with the true business value it brings.
So why is this HUMAN factor important?
1. It assures consumer satisfaction scores: At the end of the line for any BI
project or BW-on-HANA project sits a bunch of humans. They either like to
deliverables or sometimes totally dislike what it provides. It is critical to
the success of all projects by assuring the technology platform is right. When
IT starts to take decisions on behalf of business owners and users things can
become a little tricky. By involving the business owners and users early
projects can substantially increase its success factors.
2. It focuses on 'business benefits' by making the technology
transparent: From a technology perspective data is going to have volume, velocity and
variety. It will be subject to machine learning, pattern recognition, map
reduction, business filtering, textual mining, contextual visualization and a
host of other filters that delineate the data and technology from the business
needs of the end consumer. Business benefit focus allows solution architects to
‘box’ the transforms into neat bundles of ‘Consumer Relevant Matrix’ designs
with a full understanding that consumers of information have different needs
and think differently than the developers who create and transform data. It
translates to that -business users have dynamic information needs that are
driven by their sphere of influence vs. IT that has a historical view of
reporting requirements based what their triad partner provide to them as
solutions or what users have been using for the last 5 years. We call this as
the CSS (Consumer Satisfaction Score) that measures the true success of any new
technology installation. According to 2012 Gartner BI report most global BI projects will have a
CSS of under 30% for the period of 2012-14.
3. It identifies the true customer: It is more than proven that the human
users in the enterprise are the true consumers and the final customers for most
IT initiatives. Gartner has been pointing this fact out since 2006 that IT has
been segregating business from BI project decisions, and that business
stakeholders need to take ownership and accountability of their investments.
The human focus allows projects to deploy BVA (Business Value Attainment)
methodologies that have consistently raised end suer scores from their current
20-30% to above 80% simply be adopting a different methodology and roadmap to
deploying IT solutions – mainly those dealing with BI and Analytics.
The Strategic mindshare starters are
1. STRATEGIC BENEFITS: how do we protect strategic
investments based on decisions taken today?
2. IoE CONSIDERATION: Audit every selection through the
strategic enterprise IoT and IoE needs across the full value-chain.
3. HUMANIZING: Replacing cold technical deliverables with warm ‘business
benefit’ and user friendly ones by training and involving business stakeholders
into the process.
4. BVA Impact audit: Audit every report in the production
system for its ability to amplify business benefits, outcomes achieved based on
actual user inputs and output signals from across the full value chain. Leverage
CSS scores to measure true success of initiatives.
5. Leverage Business Benefit Force Multipliers: The solutions are clearly written on
the walls the only issue is as to how many of us, as key decision makers, are willing
to read the obvious.
These Force Multipliers come packaged into half-day workshops, executive one page checklists, IQDCT methodologies
along with automated tools for remodeling, re-coding custom ABAP and accomplishing system mergers, i.e. merge multiple SAP system into 1 prior to HANA migration.
Actual Results achieved: At one of the world’s largest BW on
HANA customer we reduced initial HW and SW investment by 68%, we reduced BW
size from 97TB to under 20TB, we reduced NRR (New Run Rate on HANA) from CRR
(Current Run Rate on BW) by 22%.
At another retail customer we reduced the HW
requirements by 52% with a 1 day workshop and 3 weeks of workshops with their
SI Basis leads.
At still another customer we merged 2SAP ERP system intone while in production, At still another we merged three regional BW systems into one prior to moving to HANA.
So as you take, plan to take, or after
having taken the SAP HANA leap- it is your choice to make this yet another leap
of faith or one based on scientific principles leveraging proven best practices
that deliver the highest quality at the lowest cost and in the shortest time.
