Enabling Business with an intelligent Business Intelligence strategy !

The company had faced challenges due to change in leadership positions often due to bad hires across positions; decisions were made based on bravado and far-fetched stories that even the naïve would find hard to believe. The pseudo leaders in turn hired a coterie that would make them look good in meetings and talk about the glorious past that remained unverified. The rot at the top soon started bringing results commensurate to the collective intelligence applied to the problems and opportunities at hand.

In a growing market loss of market share and dive in profitability for a steady business could not remain unexplained for too long; the growth agenda and strategy that was outlined with help of big management consultants was quickly challenged by equity analysts while the shareholders listened to the stories with unease. Nepotism running rife through the ranks led to collapse of meritocracy – some becoming victims of their high professionalism and others weeded out as they individually threatened the collective brainpower.

The stock price which had tasted peaks with the induction of the new team started a slow and steady slide shaking up the promoters and the Board, to sit up, take notice and do something about it. Failure of cronyism resulted in tumbling one after another like ninepins but not before they had shaken the foundations of a company that had withstood market uncertainty and thrived in the long history of the industry. Few of the inept skillfully hid themselves from scrutiny and survived the expungement of undesirables.

One such survivor was the CIO who successfully portrayed herself as a critical resource and managed to save her band of followers too. She misrepresented past ties distancing herself from those out of favor; those under her patronage followed the leader saving their skin as the rest of the team watched in amazement. They rode on hard work of few good people, quick to claim credit while ensuring that no voice was raised or heard against their tribe as they strengthened their feeble position step by step.

Taking control of the situation the Patriarch emerged out of retirement and hired fresh management team to take over the shambles, revive and restore the rightful place in the market. Staying out of sight during the initial reviews and analysis, she slowly emerged from the shadows to stay out of the limelight lest her highest level of competency fall short of the rising baseline. The enterprise trundled along recovering some lost territory but struggling in the absence of accurate and timely information from the transactional and reporting systems.

Under the spotlight she promised to create business intelligence strategy to help the company in taking better and effective decisions. The task being beyond her intellectual capacity, she felt prudent to hire a big name consulting company to formulate a plan that would save her skin and earn some brownie points. Budget for the exercise was sanctioned and the consultant brought on board; as they got started an unaligned team mate who was the mainstay of existing business and financial reporting quit.

A specialist was brought in by the consulting company who understood the industry as well as the technology adoption curve for similar enterprises. Within no time he had captured the current state of transactional, financial, sales, and other functional reporting, which was quite basic. He evaluated the tools and technologies, inventory of licenses available, and called a meeting with the CIO and her team to discuss the future roadmap, vision and direction, and get an insider view of the challenges and opportunities.

She started off well, but…: I want to outsource the entire analytics and operations while my team can focus on what matters to the business. My team lead has quit recently and due to that there is a void that needs to be filled. You know we implemented this new ERP system last year and then we also invested in this big name BI tool, the implementation of which is still going on, and my BI lead has quit. I want a strategy for which report should be served from the ERP system and which one should come from the BI system.

The consultant did not know whether to repeat the question or accept the answer at face value; as he mulled over the response, the silence was broken by the CIO again: Why are you confused ? We developed over 200 reports in the ERP system, but hardly any are in use; most users want a data dump and then use it in spreadsheets. The management is upset as the inability of the investments to deliver; which is why I need your help to understand which reports we should retain and which we can move to the new system !

The next day the consulting company withdrew from the engagement !

Data, data everywhere but what do we do with it ?

“Can we do something with Machine Learning, Neural Networks, Deep Learning, Artificial Intelligence, to be better than our competitors or disrupt the market ? We are growing faster than the average, but I constantly fear where the disruption will come from to our industry”. Thus spoke a technophile CEO of a mid-sized multinational company. They had grown inorganically acquiring brands, products, and small companies in growth markets to grow and increase their product portfolio to stay relevant to their customers.

It is an exciting time to be in the technology world with technology at the center of almost every disruptive thought and asset light digital business model. It is an exciting time to be a consumer with everyone bending over backwards wanting to provide offers and promotions on anything and everything. It is indeed an exciting time to be an entrepreneur with unimaginable ideas beginning to take root and come into the realm of possibilities with fast evolving technology allowing for rapid prototyping and success.

It is a mobile first world where everyone wants their App on your phone, send you notifications, read your address book, track your location, and gather petabytes of data to analyze to eternity. Data is everywhere, it always was, though not in a form that could be capture effectively, assimilated and explored. Technology has evolved allowing semblance of sense out of stray wisps of information in the large volume of data to form pictures and scenarios; newer insights, action items progressively improving outcomes.

Big data is getting bigger, analytical tools are evolving rapidly, compute is getting faster, storage and retrieval quicker, and business hungrier for data driven insights. Democratization of technology and availability of tools creates a perception of easy pickings which continues to add to shelf ware for the IT organization. CIOs are being pushed to create new centers of excellence or hire skills that will help make the business grow faster and more profitable; consultants are filling in the gaps across the value chain with limited value delivered.

Internal innovation and new ideas are nurtured in few enterprises, this was not one of those; the company had always rewarded subservient behavior with stray incidents of brightness escaping attention. With a cautious approach to every spend in the past, managers were unable to rise to the occasion fearing being snubbed. The technology organization had decent set of tools, they were well aligned to operational IT requirements, but limited expertise and ability to shift gears into a new level of thinking and execution.

The CEO threw the challenge to the management team to come up with a plan on how the company can break away from the normal. Two quarters later there had not made any significant progress or breakthroughs. The CEO thus hired a global top consulting company to help create the roadmap for digital disruption. After three months of Workshops, brainstorming sessions, offsite and many weeks spent in conference rooms, the exercise was declared complete and the management team invited to unveiling of the new strategy.

Sounds familiar ? This is the story of almost every enterprise where information is consumed in reports from traditional ERP systems or data dumps massaged in spreadsheets. Scores of reports with columns represented in different places or one additional data element make up the repository of analysis. Smattering of dashboards at Board Meetings, Investor Conferences, and external presentations represents the visual data creation and consumption. People love their prints but also want tablet computers !

A big hole in the pocket, they had a document with multiple streams and action items; teams were created and tasked to generate new customers, markets, and disrupt competition. The consultants stayed on to oversee execution and find faults; they churned dashboards, progress reports, control towers, to keep telling the management why they had still not achieved the desired results. A year later and a bigger hole in the dwindling treasury, breakthrough success continued to elude them as competition grew fiercer.

A new age company CEO reaffirmed the hypothesis that data is the future lode mine proclaiming they generated and consumed a petabyte of information daily. His business added new revenue streams every quarter, evolving with consumer demand while shaping the market. His company had redefined the industry becoming the benchmark, taking calculated risks and staying close to the ground through the journey. He did not scoff at the old, he just decided to create a new path giving his team freedom to explore.

Can old age companies emulate such examples ? There are a few examples, but still a few; survival is not threatened for most, relevance probably is !

My Refrigerator has gone shopping !

I was at this conference where one of the streams focused on Internet of Things or as some speakers preferred to call it Internet of Everything. Every speaker had statistics on the number of “things” that will connect to the Internet and communicate with other devices or the Cloud; the number range varied from 25-50 billion depending on who you would like to believe. The “things” with intelligence could be for specific tasks or multi-faceted to do a range of activities like personal health monitoring, cooking, cleaning, etc.

Every speaker without exception talked about smart refrigerators which will connect to the nearby or your favorite grocery store and proactively order provisions you consume and debit your credit card/bank. One of the speakers dramatized the situation with driverless cars going to the store getting filled by a human. The collective hypothesis was that this is no longer science fiction but reality as it will pan out by 2020, the year by which the number of 25-50 billion devices would be reached; cars, fitness bands, microwaves, light bulbs, interesting thoughts !

As I thought about it I wondered about the situations in my life. For one I like variety in my food and cannot imagine eating the same stuff every day or week. Probably the refrigerator can be taught to have variety. I also don’t want stuff ordered when I plan to eat out go on vacation or call friends over for a dinner; maybe calendar integration will solve the problem to some extent. I hope that leftovers management, use of partially used open packs and managing short expiry products is part of the functionality.

Let us assume that the refrigerator is intelligent enough to not order one item at a time and creates a list of item taking care of minimum order quantity or bill value to avoid unnecessary shipping charges. What happens when the store does not have the items or in the pack size that I prefer ? Will the store substitute another item ? What if I don’t like to substitute ? The store supply chain is probably connected to suppliers’ warehouse system which through predictive analytics understands demand forecasts generated by connected refrigerators.

I am a shopaholic and love to spend time in the stores. My young daughter who grew up traveling in the shopping carts still wants to go back occasionally to now push the cart that was her vehicle. In most of these trips we end up buying a lot more than what we had planned. The visual merchandising appeals to the senses and impulsive buys are triggered by material and inane offers that scream at you while you walk the aisles. So what about cross-sell and upsell that is the hallmark of a good store which entices you to fill up ?

If the above were to translate to reality all the high street and neighborhood stores would struggle to survive and probably turn themselves into warehouse type stores which don’t need a storefront. It would significantly change the way we shop and ruminate over products on the shelves where we can compare not just the price but other attributes. Packaging could be dumbed down to basic, no need for creative colored eye catching wrappers. How will marketers of new products reach out to me on TV or print when I rarely walk the lanes in a store ?

Maybe big data analytics would churn offers to me on the screen of my choice from which I could put it into the refrigerator’s shopping list. I hope that the cold creature (refrigerator) will know its capacity to order only as much as it can store adjusted to my variable consumption pattern. I wonder if my Robot can take out the right quantity of ingredients and cook a meal that I browse and drop it into the task list for the mechanical cook and keep it hot for me when I arrive home. Maybe I am getting a bit ambitious now in my expectations.

The one thing I could not fathom through all the presentations; the bright and intelligent refrigerator knows what to order; the store knows who the order comes from, the car knows where to go to pick up the groceries and brings them back home. I stay on the fourth level of an apartment complex. How do the packages get to my apartment and inside of the refrigerator ? Now don’t tell me that the Robot will do the job, as it would end up compromising the security of the house ! Even a dumb crook will see the pattern and break the system.

I hope you can fill in the missing link for me.

Data, data everywhere

“They want 78 new reports from the EDW and Big Data which has taken more than a year and a major part of my budget to build ! They already have hundreds from the transactional systems which are printed on reams of paper which no one reads. All the Excel sheets that they were churning out from data dumps from various systems and a bit of external data get into management meetings where everyone has a different number”. Looking at the CIO I sympathized with his predicament, it was a familiar story.

We all have at some time or the other been frustrated with endless requirements of reports and data dumps from all and sundry; lot of effort is spent in analyzing the past and validating hypothesis on what worked or what did not. Requests flow like rainwater on a slope, never ending stream many similar to others from neighbors at workplace not talking to each other. Reports get built for a casual question in a meeting never to be used again; when another one pops up from new quarters, the effort is repeated.

We hear of associations, correlations and insights not possible in the past as we did not know how to combine an apple and pineapple to get a watermelon. Structured data was easy until we started going to multiple sources with limited commonality. Even then with statistical models diving through seas of data, the proverbial needle could be found in the haystack. People buying napkins buy beer, not vice versa; owners of red cars have a higher propensity to be rash drivers, and so on. You could correlate anything to sunspots !

Not too long ago the need to explore unstructured data began and with social media explosion the dimensions for analysis changed. Thus Big Data began its journey to challenge conventional way of looking at data and information. Jumping on the bandwagon the term was hyped by one and all to include variants that stretched imagination. Came along new skills everyone thought were important for the future: Data Scientists and Chief Digital Officer to name a couple; did such a species exist or it was glamorized plain old profiles ?

Moving from hundreds of GB of data to thousands of GB does not make it Big Data. The amount of data being created and added to corporate storage is growing exponentially. Data types are also expanding with technology offering ways to mine it. Dashboards and cubes work well in selected situations, their action-ability is still wishful thinking. Enterprise manager thinking has yet to evolve beyond reports from transactional systems; thus the data scientist continues to remain a glorified report writer.

The CIO narrated his woes which started with the Company Board approving a really large budget and unrealistic expectations from the project they called BBF (Bigger Better Faster). With much fanfare the project was kicked off, many people inducted into the team and a few pretentious youngsters hired to lead them to gaining insights thus far unknown, from this prestigious first of a kind in the industry Big Data project. The CIO kept his reservations to himself knowing his meanderings would not be given a kind ear.

The project team got bigger faster than anyone thought possible; the technology they bought was deemed better than what they had. Everyone loved the progress they made in the initial months. Then started the reality check with the target audience (managers) putting across what they wanted to run their business better, to grow bigger and reach out to customers faster than their competitors. Challenges with technology and data consistency appeared small compared to the change required in the mind set within.

Activity Reports on social media, portal registration, access reports, keyword searches and some more were the peak of expectation. There was no marriage between the old and the new as if they lived in separate worlds. What could have been remained buried somewhere while everyone wanted better and faster transactional or tactical reports. The rich stream of data that could have been big for the business was diverted and converted into wasted effort. In the corporate world, I believe that the overwhelming data deluge is far from being tamed.

Do you know different ?

Ignorance to Intelligence

A sparse gathering of smart people in a small room were discussing an important business hoping to change the outcome in their respective circles of influence. These were seasoned players in industries big and small across diverse geographies and line of business. It was crowdsourcing at its best and that gave rise to the expectation that the problem will indeed find itself vanquished. No I was not the fly on the wall or a passive listener; I was called in to moderate the discussion.

When I joined the group, they had already listed down the facts and figures about the rate of success that they had captured from published research as well as search engines. Anecdotal references were discarded focusing on empirical data and reference case studies. They had also listed down challenges and issues based on their real life experiences. The consistent and clearly emerging message was how to get Business back into BI, while the “I” actually stands for Intelligence and not Ignorance.

One of the discussion threads went something like this: the CEO needed quick reports and analysis of business with the ability to drill down; he also expected the ability to slice-dice the data. The business head wanted control over her team and did not want the CEO poking his big nose. IT simply wanted to buy the best tools since they did not have control over the environmental and political factors. The CEO in a social meeting was sold on the merits of a frightfully expensive platform and that was that.

The tool was bought, the wish-list generated across different stakeholders top down, the scope defined and captured by the principal vendor, and the execution outsourced. The requirements were skewed in favour of reports and very few dashboards or analytical cubes and that was deemed okay; everyone agreed that the phase two will cover the rest. So with a lot of fanfare the project got started and everyone believed that the future holds a lot of promise.

Through the discussion no one challenged the ask, no one sought to understand the impact of the multitude of reports on the stakeholders, no one challenged as to why the operational staff was not in the room to define what they wanted. The executives in the room blissfully proposed the metrics and data that others should be seeing, reality being far removed from the proposals. The few dashboards that were to be consumed by the CXOs changed shape based on assumptions of what they would like.

Running through the discussion I realized that this specific case had all the ingredients across the various representatives, so the solution could be broad based to apply across. Good news is that it was not a technology project considering initial active participation from the business, however they had disappeared post initial discussions leaving the baby with the vendor and the IT team. With the sketchy picture the solution was unwieldy and unusable across the layers of management and operational staff.

My submission to the team was to go back to basics and start asking some tough questions and not to proceed if the answers were not up to the mark. Their lack of enthusiasm depicted their unwillingness and inability; with some persuasion they agreed to plunge ahead. As we discussed the questions and the approach their eyes gained the missing spark; the conclusions were agreeable to all present as the best way forward. Here’s a synopsis; report is used as a representation, it could be a dashboard or cube too.

1. Why do you want this report ?
2. How do you get this information today ?
3. Who else could benefit from it ?
4. What will change for you after you get it ?
5. Which personal, group or company KPI (e.g. customer, employee, revenue, profitability) does it relate to ? How ?

As we closed the meeting, I realized that earlier some of these questions had got me into trouble from which I could extricate myself from with some effort. The project was however declared a great success and a case study by the company, vendor and the industry. I believe that it is a better place to be; ignorance to intelligence is a difficult journey. Educate the business; don’t get bullied into accepting inane requests for reports that can be fulfilled by transactional systems. Someone has to drive it, why not you ?

Intuitive Analytics

It was a packed house listening to a panel discussion between two CIOs, a CEO, a vendor and an academician. After almost an hour of discussion on various aspects of Business Intelligence challenges and opportunities, the session end requested final words on what they would like to see from vendors in the future ? Leaving aside the Oscar-ian twist on being good to customers, better decision making and paying more attention to talent, the crowd applauded unanimously to the CIOs wish list. The CIO representing a “mature” user of solutions from the sponsor BI vendor, made a passionate appeal:


Has anyone in the audience attended a training program on how to use Facebook, or any other website or messaging system ? If no, then why do we require everyone even with above average intelligence in the corporate world to be provided training on usage of internal systems ? What makes these systems so complex that they cannot be used without handholding ?

I wish that we can all evolve to a level of BI/DW tools such that any user within the enterprise can start using transactional data to convert to information that can assist informed decision making. Anyone who can use a spreadsheet should be able to extract the insights hidden within the sea of information. They should be able to intuitively understand what is expected from them to get to the next step with no prompting or help (online or otherwise). I am talking about Intuitive Analytics, a term coined by me a while back to refer to analytics that is intuitive in its interface; intuitive to the user the way s/he is able to open the browser on the PC, Smartphone or tablet and start the journey of discovery on the Internet.

In recent times there have been multiple initiatives around improvement of how information is presented to the consumers. Evolution from rows and columns to dashboards, drill-downs, pivots, multi-dimensional analytics has evolved; the evolution of mathematical models as well as technological advances on speed of crunching data have pushed the boundaries across enterprise datawarehouse projects. Over the last three years, DW/BI has consistently been in the top 3 technology and business priorities.

The experiences are however inconsistent in their delivery of business value. Some of the barriers include data quality, data model deficiencies, bad ETLs to name a few. The biggest deterrent has however been the complex user experience which has seen lesser evolution as compared to the technological advances. All tools with no notable exception provide the basic building blocks to create the DW/BI foundation and analytical layer; standard templates, internal IT teams and implementation partners have yet to breakout from the mould to provide a rich, consistent, and meaningful capability to the end consumer of information.

I believe that this is an opportunity for one and all, CIO, DW Architects, vendors, implementation partners, to take up this challenge on making BI as easy as getting on any social media site and get started. If you have already crossed this bridge, do write back, but the applause on the floor to my comments, makes me believe that the journey is still more like an uncharted expedition.

Return on Investment, Intelligence or DR

Considering that almost everyone is at some stage of the next year’s budgeting process, ROI has been dominating mindshare. Amongst these were two discussions around return on Business Intelligence and return on Disaster Recovery. Both are fairly nebulous in their manifestation, and difficult to put a fix on the number that can satisfy the CXOs, especially the CFO and the CEO.

Business Intelligence is a discipline that as an enterprise orphan suffers from detachment from its real users and owners, largely due to the technology’s complexity. Thinking beyond conventional reports to analytics is a leap of faith, and the enterprise’s ability to formulate and use trends and associations that are atypical. In the flurry of operational activity, discretionary time is a luxury that many can ill-afford. Thus, most organizations end up with expensive automated reports which serve the same purpose that ERP reports did earlier.

Disaster is something that strikes others; so why put aside significant investments, time and effort that could be used to create new capacity or build additional capability? With a few exceptions, almost everyone has a disaster recovery plan on paper nominally funded, rarely tested end-to-end, and seen as an item necessary to pacify the statutory auditors. Should an untoward incident strike, the ability to retain continuity of business would not withstand the rigor of time and process.

In both cases, continued budgetary support is seen as cost and not as an investment. The discussion on ROI is thus fraught with danger avoided by the CIO, challenged by the CFO and others. Is there a way out of this predicament? Definitely yes, but it requires the CIO to approach the discussion a bit differently maybe play a difficult hand; conventional dialogue will not change the outcome.

One track that some have used is to debate the absence of these solutions, what it implies and the associated risks. Absence of BI may probably not be treated with the respect it should, as transactional reports are also possible from the ERP systems and the belief that everything else can be done in a spreadsheet. So a BI discussion has to be guided towards the benefit to different stakeholders and possibly transferring ownership to one of the business CXOs. IT should not be the driving force and implicit owner. After all, the starting point of BI is B-business.

The absence argument has better traction with DR; with the primary systems being out for a period of time, the impact with varying degrees will be felt by everyone, irrespective of industry segment. The time to recovery will decide the type of DR option to be executed. DR is also synonymous with insurance. No one wants to die, but almost everyone buys insurance. So if the data center were to pop it, DR does step in and take over (hopefully, and that is where the discussion went awry).

Are there any models that can be universally applied to formulate ROI on BI and DR? Unfortunately, even those that exist (perpetrated by vendors or consultants) are being challenged to shorten the payback period. Innovation is pronounced after success is evident else the debate will get ugly. We all know that “insurance promising ROI” is not insurance, we are paying more than we should.

The Business Intelligence Challenge

The term Business Intelligence would imply the "intelligence" that "business" can create and use with help from tools and technology orchestrated by the IT team. Many billions of dollars have been spent on this journey across industry verticals and an equal number of technologies, broadbased or niche, with limited success.

Over the last few months with new projects hard to come by, the focus for many enterprises has been to improve decision making with the help of insights that can be delivered from existing data marts or data warehouses. This is off-course expected with no additional funding. Business Intelligence has also featured on CIO agendas researched by many marquee research entities.

Thus vendors have been getting quite aggressive in their sales pitch claiming to have all the magic formulae towards achieving the elusive ROI from BI as well as improving the usage of information towards making effective decisions. Many of these vendors have staff they have hired from the industry, who worked on in-house BI projects, successful or not, but now purportedly have the wisdom on how to make it work.

The question that baffles me is that in most cases the effectiveness same consultants was at best average with a few exceptions. What has changed that now gives then the insights from the outside to create exceptional performance for their customers ? Talking to them rarely gives one the comfort that they will be able to indeed drive through the change and create value irrespective of what their PowerPoints may depict.

The technology or tools do not appear to matter to this brood. The list appears like a menu card in an expensive restaurant which also includes esoteric dishes with fancy prices. And if it is not on the menu, don't worry, the chef will create what you want (custom solution).

Why is it that "wisdom" on how and what on business intelligence is with the consultants and vendors and rarely manifests itself within the enterprise ? I scratch my head and all I get is hair ! I am now losing it faster with the number of BI shops mushrooming everywhere. Maybe I should think of joining the herd rather than trying to beat them at their game.

BI OIC for CIO

Business Intelligence has been on the CIO radar for over 3 years now as per research reports from the major and respected IT research companies. Billions have been spent by companies and as a category, BI projects have seen the least success across almost all IT enabled initiatives. BI consultants will go about advising you that they "know" how to make it work for your enterprise and if and when things start faltering, it's always you and your users who are responsible. I happened to ask a VP turned consultant from a large bank, "How is it that consultants have all the answers, but employees do not ?" and got no answer.

Every organization aspires to create intelligent insights from transactional data and act upon them to increase revenue, optimize profits, retain customers or create efficiencies. In most cases, users are unable to think or visualize what they want to achieve any of the above objectives and thus end up defining extremely complex scenarios and reports with a hope that they will provide some kind of "Eureka" brainwave and they will be heroes. IT organizations takes limited steps to dispell such myths and takes on the task of creating models that enable the complex reports. Maybe because they are not in the bath tub !

Typically such operational data based reports provide limited insight since the insight is driven by humans and not systems. A report viewed by different people creates different inferences and that a technology cannot provide. Technology works on models created by us and is thus limited by the information gathered and understood by the developer. This indeed is the key to actionable insight and the experience and frame of reference of the person which makes the difference.

This is not a great insight, but it is based on the experience of seeing many business leaders responding with differing insights to the same analytical report presented. It comes out of a deep domain expertise and lateral thinking. Such individuals if enrolled into the program can make the difference between a successful and not so successful BI project.

Left to IT organizations, which is the typical case with BI projects, the end result is multi-dimensional reporting which is finally used to review business but with limited insights. It is evident and obvious that right people make the difference, but the right people are normally too busy to spend long periods of time to understand the possibilities and list them down. If by chance that were to happen, the adoption by the rest of the organization suffers and gets blamed on bad "change management".

So what is the conclusion ? A few "actionable insights" based on 3 BI projects.

1. Find the "right" person within the company who can help create insights. It may be your CEO ! If you cannot find such a person, don't start the project

2. Start small and scale up as you taste success; before you attempt to build the Taj Mahal, practice some smaller buildings

3. Tools and technology matter, but in the end, the data quality makes the difference

4. Do not be averse to restarting from scratch in case the first model or the second model does not deliver. It's quicker to recreate than attempting to patch a bad one

5. Keep on asking questions at every stage, "Why do you want this ?", "How will it help you or the company ?", "Who else can benefit from this ?", you get the picture .....

6. Whatever you do in stage 1 may need to be discarded by the time you are in stage 3 and that's okay.

Gartner CIO Summit

Today was the last day of the Gartner CIO India summit at Mumbai. The difference which i found from the earlier CIO gathering events is worth noting from Vendors Perspective.

1. It was a paid event for CIO 1000USD. It gives a focus serious audience.
2. It has multiple round table tracks hence focused sliced audience was available to the vendor
3. Gartner had selected limited vendors for sponsorship.

In fact we were shocked when they refused us the sponsorship mentioning that they were sold out. The event content was research based and had one on one sessions.

Nothing in this world comes free. If CIO time is valuable and in shortest time they would like to grasp maximum technology and business value then only option is to pay to Gartner type events.

On business intelligence front the domain where in we are working is now becoming the top priority for CIO across the board. We had an overwhelming response from all vertical across the industry due to our participation at CIOL C-Change 07 and IE Technology Senate. It means that CIO present at that events were benefited by attending the event as they got exposed to a new value proposition in BI space.