Dec 18, 2014

Mistakes To Avoid in a SAP HANA Initiative

Smart, connected products, machines, devices and operational data sources all have the potential to offer extremely rich, and valuable, opportunities for business benefit creation and exponential growth opportunities. However, efforts to seize these opportunities seem to be getting quite elusive if Gartner reports are to be believed.  
Agreed, these new disruptive technology opportunities, like SAP HANA,  will not come without challenges, yet there are some very simple strategic outliers that have the potential to provide the highest benefits to global enterprises taking the SAP HANA leap. The key is to work with proven scientific standards and processes and not get dazzled by neon lights of promises built on the ashes of the last generation technology enablement.

Some of the greatest strategic risks for SAP HANA initiatives include the following:

FOR BW-on-HANA  MIGRATION CLIENTS - (apply similar rules for SoH)
1. Not estimating the strategic benefits of HANA: Most customers that we worked with, over 19 migrations were moving to HANA for one of two, and often both, reasons . [1] Real-time visibility to very large date sets (internal big data); [2] A desire to dwell out into the www. to collect streaming data, customer sentiments, enterprise contextual nuggets out of the world of Big Data.  So without realizing customer are firstly betting into Big Data (step 1 internal and step 2 external); IoE (Internet of Everything),and then SAP HANA. Companies that simply jump into HANA without strategic considerations of Big-Data, IoE integration and HANA will firstly waste around 50% on initial start up and then may times over as they reach new stages of inevitable maturity.

2. What Got you Here Will Not Get you There: It is important to dwell on the Gartner reports of 2003 and 2012, dwell very deep indeed. Here is defined by a PRD environment where more than 70% of reports are not being used or will never be used by your business users. Facts show that the larger your Partner the harder they find to adapt, and change, to meet the requirements of the new SAP HANA platform. Their 'expert' minions will take years to adapt to the new HANA platform- during this period they will continue to deliver the same stuff that has got you here. So your safeguard is to find yourself a SAP HANA Business Benefit team with experience in BVA methodology with the BVA  acid test process.

3. Treating HANA as just another Technical Install: Our message continues to be - HANA is a strategic business solution and not a technical install.  Yet, a rather large percentage of HANA migrations, especially the BW ones we have been tracking were done more as a technical upgrade. The signature of these migrations is 'As-Is' migration, i.e. lets rapidly take your current BW environment as-is to HANA. These companies have just wasted a minimum of 40% on their initial cost for HW and SW and will continue to pay an average of 40% more annually on support SLA's.

4. Underestimating Strategic Partner Risks: Selecting your HW & SI partner because they have been your partner I the past resonates with point #1 & 2 above.  When moving to the new Big-Data, IoE and SAP HANA platform think HANA4IoE. For more details view the HANA4IoE event in Palo Alto on Nov 11th 2014. Ask your HANA SW partner about IoE questions to build SMART or INTELLIGENT enterprises, industries, Farms, Hospitals, Planes, etc. Select your HW partner based on their experience in networked and communication devices because with a SAP certification all HW providers are kind of similar (other than the 'mine is bigger' statements one may find). However if you done need a 100TB appliance why think along those lines. Select your SI partner based on their focus on new HANA methodologies, ways to guarantee 40% reduction in TCO, ROI comparisons, automated tools for optimization-and not simply their size. Think Big-Data, IoE and HANA when selecting your Triad partners and no less. Ask them for Business Benefit deliverables. Demand the BVA Acid Test deliverables for your SAP HANA.

A. Not estimating the strategic pitfalls of your HW & SI partners: Most new customers in 2014 and possibly 2015 will be the large customers. Large customers tend to prefer what we term as Tier-1 Partners.  So for their HW and SI partner their natural choice may be incumbents or companies with large names. This is an excellent choice, however, these companies need to also understand that a lot of the Gartner surveys may have been  the result of these very Tier-1 companies and their inability to change to the strict 'Business Benefit' drivers that Gartner has reported in 2003 and then in 2012. You can send the author an email to the 2012 Gartner report interpretation.  New companies that simply jump into HANA without strategic [1] quality assurance checklists and audits,  considerations of Big-Data, IoE integration and HANA will similarly waste around 50% of their assets on initial start up costs,  and then may times over as they reach new stages of SAP maturity.

B. HANA is not just another ERP, CRM, SCM, or BW install: Most of the large companies have 10 to 30 thousand SAP resources that have been implementing SAP from the time SAP started. Most of these 'experts' have set ideas to SAP standards, processes and global methodologies. Most of these companies will find it pretty hard to retool their 10 to 30,000 resources to the new SAP HANA platform. So what you will get is a lot of old thinking that will begin to dive your new platforms. As a new enterprise you do not want to take your organization to the Gartner nightmare, point 2 above. Despite every assurance the main question is how will you safeguard your self from this possibility. You do not need most of the things that drove the traditional SAP ERP, yet there is a small likelihood that you will be driven down that same legacy path because your 'experts'  know no better. You need to safeguard yourself from waste, abuse and ignorance about the optimal standards, processes and methodologies for SAP HANA. [1] Ask your partner to work on the BVA methodology for your BI initiatives and apply the Acid test for deliverables; [2] To start with find yourself a neutral trust-worthy HANA Business Value Architect whose sole job is to protect your business value  as your neutral right-hand advisor if you are the project owner.[3] Ensure your advisor is someone that you can trust and that is working  only for your and your company's business interests without any conflict of interest. Its a small expense that will save your many times over in waste and headaches.

i. Adding functionalities that you do not want to pay for: You need to tell me the business benefit of taking a report that used to take 715 seconds and accelerating it to 2 seconds if business will never use it. Performance alone is nota great reason to move to HANA. Just because HANA will improve performance 3, 5 or 10,000 folds does not guarantee your business benefit will be high. Taking 70%of redundant objects and reports to HANA will reach a point of diminishing returns - sometimes rather rapidly. We have been delivering some RBS (Rapid Business Solutions) for HANA customers as 100% custom analytics driven by business owners. This has consistently resulted in users satisfaction scores of above 85%, 20 weeks after go-live.

ii. Underestimating your Big-Data, IoE, & Security impacts: As you mature with HANA Big-Data will inevitably come into play. As you mature in big-data you will into your machines, transport, partner production lines and their devices that produce data and rapidly enter the world of IoE (Internet of Everything). As you enter the world of IoE you will need to open your firewall doors to venture outside your safety zones. as you venture out of your Firewall you will face a minion of national, enterprise and singular hackers and viruses that you may not be ready or prepared for. You need to plan for all these stages today. Smart, connected enterprises will need smart network and communication devices and products. These in turn will open major new highways into the corporate infrastructures, systems and data. All this mandates you plan for this from today with partners that are global leaders in 'Single Pane of Glass' solutions for application security along with network security, device security sensor security, communication security, information security and content security (don't want to become something like the Target or Sony Hack).

ii. Underestimating competitive and alternatives threats. : On the competitive advantage positioning your competition could right now be starting to offer smart, networked products and services which can rapidly reshape the definition of your industry like what Amazon did to book retailing or digital imaging did to photography, films and reprographics. On the Alternatives advantage positioning you could chose HW partners that are strong for inside enterprise firewall solutions but are a security exposure for IoE and Big Data scenarios. They could be selling you black-boxed appliances that your IT cannot touch and where support costs are through the roof, while you may have a TDI option for best in world class options for a maturing SAP HANA. You could partner with a SI partner that plugs a school bus of legacy resources for your HANA initiative in a platform where your IT or business knows almost nothing. You could end up with a landscape that that is 400 to 700% of you maximum requirement because your team knew no better. New technologies and platforms like SAP HANA almost mandate you look at new partners in order to take a professional decision. Disruptive technologies have a pattern of tearing traditional partners, yet those that pursue incumbency often pay the price along the way.

iii. Spending too long planning: Spending too long to move into Big-Data, IoE devices and/or SAP HANA may slowly erode any competitive advantage you have in your market or industry. Competitors that move the fastest will be able to provide higher quality, more connected analytics at lower costs- and you want to be that competitor. Some large SI's are known to pend months and years in planning and discovering what the enterprise needs(especially for new HANA customers) and quite often by the time the audit is completed the market has already moved and the original business needs are no longer  relevant. Just like ideation we can no longer plan for years, design for years and then launch a product. We need to ideate and get to production in 9 to 12 months. The days of years of planning are long gone. Now we need to move rapidly. In a world of big-data and  Real-Time business we cannot take three years to ideate. Think Scrum. Think one step at a time.

So remember SAP HANA is a Strategic Business Solution and not a technical install.

You can only get to the destination that you plan and approve. So plan your work carefully before you work you Plan.

Dec 3, 2014

Is IoT +BiG Data making traditional polling obsolete?

Big-Data and IoT are changing not only the definition of industries but proving that polling is now an obsolete methodology; It's Time for Customers and Marketers to Rethink ‘Digital’

Whatever side you stand on the controversy over polling results continues on a daily basis. You are likely to agree on three things.

1.     The first that all polls can be designed with specific question to derive very specific results

2.     The polls of the democrats are consistently  different from those of the republicans

3.     Both polls cannot be right

So after decades of polling and despite the confusion it creates in the minds of everyone involved with its designed creation, the polling itself and the results –polling has come a long, long way and I a primary job of some companies. However a recent book and what it reveals now proves that polling is a dying process that is rapidly being replaced by digital processes that are changing the very game of ‘Who we actually are?’ and ‘How we actually think?’

I presented this on the Nov 11th ‘HANA4IoT’ event at SAP Palo Alto and thought it prudent to share it with the community because of the large number of emails I received on these few slides.

For traditional polling and marketing companies this may be a big transition. After all digital analytics has been the domain of direct response and access, whereas with traditional polling one needed teams of pollsters in select geographic locations. There is no doubt that there will be no shortage of traditionalists who will find enough reasons to stay the course, while the digital marketing and analytics will continue to be a direct marketer’s dream come true.

However, it is critical to remember that in a poll we mostly get what the polling person wants to get and we never get the whole truth. If you stop a person on the street and ask randomly ask them ‘What sex and age group interests them the most in a dating site?’ There is a high probability that most respondents will not tell the truth.

Just in the same way when we poll business users in a post go live BI business users and the IT team a simple question, ‘Do the reports in your BI system meet your needs and expectations ?’ the results are always very different. However, both answers cannot be the empirical truth but just different points of view. Based on our twenty plus years of BI implementation and support experience where is the average you should generally expect to get. [1] 20-30% satisfaction scores from actual business users; [2] 70-90%satisfaction scores from IT resources; [3] under 30% from Gartner report based on feedback from over 2,500 CIO’s globally. If you feel you have the integrity to be truthful take this poll and tell us what you think. (Remember if you lie then you prove this blog correct, if you tell the truth then you may face the reality Gartner and I have been preaching about since 2010).

What we are finding is that the reality is not on who we say we are but in what we actually do, and even thought the industry is still latched on to the last click, the truth still will hold sway. So while today there is a lot of focus on that people say the future lies solely in what people do. So rather than the top funneling their results into the poll questions and the way they could be answered, the future is dealing with life on the EDGE where people actually do what they do, without being asked what they do nor why but simply the reality of what the reality is ‘As-Is’

Here is the crux of this blog from a book I have recently read called ’Dataclysm’ by Christian Rudder who is one of the president and co-founders of a site called OKCupid- a dating site like, etc. As a Harvard graduate in math’s he delved into the data side of OKCupid and of humanity. The book reads like a thriller and the results are what prove that polling is quite redundant. Its reality that counts. To keep it simple will let the data do most of the differentiation between polls and reality. Caveat: [1] This is based on results from Dataclysm analysis only; [2] It’s my best explanation of what I saw and interpreted and may not represent the absolute truth.

Baseline: During the process of joining OkCupid you fill a form and some of the questions deal with what you are looking for. This helps internal algorithms align you with the right match. So a 35 year old male may state (poll) that they are interested in meeting a 25-30 year old female, or a 35 year old female may say they are interested in meeting a 35-40 year old male. The analysis below demonstrates the delta between who we state we are (poll results) and what we actually do (fact).

Fact 1: Poll- women: According to over 10 years of dating data the delta between what women say and do is rather narrow. As demonstrated in this graph 20 year old women reported (polls)  that they were looking for a 20-23 year old man, just as 35 year old women reported that they are looking for a 34 -36 year old man. While a 41-45 old women were mostly looking for 39-40 year old men. Fact- women: most of the women actually viewed, communicated and met men within their specified tolerances to a very large degree. Thus the delta between polls and fact for women is rather low with regards to dating data.

 Fact 2: Poll- Men: According to over 10 years of data the delta between what men say and
do is exceptionally large. As demonstrated in this graph  20 year old men reported (polls)  that they were looking for a 20-30 year old women, just as 35 year old men reported that they are looking for a 35 -42 year old women. While a 41-50 old men stated they were looking for 35-50 year old women. Fact- Men: Here is where it gets truly bizarre and funny all at the same time. Most of the men consistently actually viewed, communicated and tried to meet women within the 20 to 24 year range. Whether the man was 20 year old or 50 year old their primary preference is to meet and date a 20-24 year old woman.

So according to reality ,this represents the true gap between polling and the actual facts on the ground, the mind of men, on dating sites, looks something like this. It a very narrowband of 20-24 year old girls that they all first want to date. So next time someone tells you that you have a narrow mind they may be closer to reality than most of us would like to admit.
Whereas a poll is a form of admittance reality has a zero bias of id or ego, right or wrong, good or bad. It simply records what is.

 So in this interesting example we scratch the surface of what people (poll) enter when they have to answer a question and then what they actually go and do which is so strikingly different that it crashes the whole foundation of every wanting to depend on polling results. As my wife likes to say, at least where men are concerned.

That’s not to say that polling will no longer be a valid medium of opinions as it shall continue, But now mainly due to the ability of some powerful groups, influencers and marketers ability in proving the direct relationship between polls and their ability to predict changes in human behavior based on poll declarations at precise times. However, as we move forward more and more companies, politicians, political parties and most of all the media companies are already becoming interested in ‘Reality as it truly stands’ and not knee-jerk answers to planned questions that seek specific results.
My aim in this blog is to continue a dialog in further understanding the link between the human id and ego, between who we say we are and who we actually are, between who we say we will vote for and what we actually do. Of decreasing the delta with our big-data predictable analytics via using social data as against random polling. This challenge is a human psychology one and not a polling or digital one. We, as humans, treat ourselves as personal brand ambassadors and what we state in polls is more about self-branding rather than the truth about what and who we actually are.

At a recent conference with over 20,000 attendees we were able to track ‘in-real-time’ the movement of attendees by conference floor and booth, the movement of support staff by individual task, density of attendees and services and most important of all the tweets about different sessions and topics even as they were being broadcast-like keynote speaker sessions. Global branding is rapidly exploding into the digital space, and the digital arena is rapidly adopting to big-data and social network analytics. IoT devices connected by a seamless network devices providing streaming data turned into real-time decision focused analytics. 
All marketing, including digital marketing, is driven by a baseline of assumptions as to what customers like to do most frequently. With new IoT driven digital marketing applications we are now reaching a point where they are able to stop people in their tracks with the power of ‘who we actually are’ and the customers' emotional experience. In other words it is now time for customers to shift their thinking from traditional polling methods to more scientific methods and get access to far greater truth than polls can ever hope to provide.  

This is not going to be an easy shift to get accustomed to or to pull off. Matching true actions in real-time response means tracing the customer journey from a bottoms-up, inverse funnel all the way to actionable predictions, through to validation of final actions. This will probably be a massive data undertaking no matter how we look at it. However, unlike polling the process is iterative and self-correcting so we never have to send out new minions out into the field and start afresh in every new poll. It will build on itself and become more and more automated and accurate with time.

Capturing this new inverted digital polling and market emotion needs new approaches that go far beyond standard the capabilities of traditional algorithms that we typically worked with.  That’s because customers now expect end-to-end analytics that often take place over months and are accompanies with branding, mail campaigns, direct tele-campaigns, and short burst efforts as we get closer to the close of the campaigns. The more real-time data you have the better you can manage the campaign, the more accurate the analytics the better your decisions become. In essence, rather than focusing on the polls and their accuracy now decision makers can focus on long-term goals, aligned to short term facts and the rapid realignment of strategies to facts in true real-time by geo location. Its hardly the process that traditional polling and marketing companies are used to.

None of these skills are rocket science, nor are they simple to develop or acquire. Traditional polling and marketing companies will continue to trudge in processes that they are familiar with simply because it is their playing field, period. But then these are digital assets that have seen tremendous breakthroughs over the past few years and are today critical for success in our new digital world.

It is now up to customers to decide if they want to embrace the new big-data and digital world that is rapidly encompassing everything we do, or stick with direct polling and marketing as we have done for the past few decades. The price to pay is obsolescence. Because no matter what you or I think the world of branding and marketing has already gone digital. Polling is the next game in town as we have moved past sending humans to the streets and asking questions to strangers with the only responses being [1] the way my questions are designed to be answered, and [2] what the respondent thinks they want to tell us. It has nothing to do with who we actually are.