What Satya Nadella hides behind his vision mobile first, cloud first?

I cannot see in the short-term to the mid-term any change in the landscape of the mobile market. There are two big players, Apple and Samsung with the help from Google. Others are doing their best to find a niche here or there. Some used, but failed tactics are low-cost smartphones, targeted age of the society, targeted market or even targeted industry. The only way to change this landscape is to the change the game rules which is happening every ten to fifteen years.

To explain what is meaning of the changing the game rules. Remember what happened in 2007 when Steve jobs showed the world the first iPhone. Apple has changed the game rules of the computing since then by introducing the super productive smartphones. Steve jobs was able to introduce a new MAC computer to play within Microsoft rules, but he didn’t do so, because he knew he will fail without any doubt.

We are waiting for the new game rules. Some experts bet on virtual reality, augmented reality and some bet on the artificial intelligence. Still, all companies are playing within the rules set by Apple since 2007,

When Satya Nadella was selected to be the next CEO of Microsoft, he changed the vision of the company from devices and services to the Mobile first, Cloud first. What Satya means by these four words? Satya knows before anybody where is the technology market right now. His decisions reflect his understanding that there is no way to go head by head with Apple and Samsung and win the battle. Then what he meant by Mobile first then?

To understand his vision, we must understand how the current mobile services are working. They have a front end in the user device which can be seen as the access point of the mobility service and there are huge data-centers contains the data (and significant level of logic). It is clear to me that mobility has two parts, frontend and backend. So, if the mobility access door battle was over, then the battle inside the room still running and Microsoft doesn’t want to lose this battle.

The mobility is a wider and bigger than devices. Although who controls the devices can control to some extent the direction of the second battle. But there are a lot of stories in the far history as well as in the recent history show how the access point controller cannot control the battle or the war in his arena. One example is the iTunes. iTunes in windows used by Apple to work as a Trojan horse to the apple echo-system. Same thing with google chrome which is heavily supported in Microsoft windows against the google decision to boycott windows as operating system (Still there is no official YouTube app in windows). But google decision is to change the user mindset from the chrome browser.

Microsoft is using the same tactics. They have more than 60 apps in google play store and in Apple iTunes store. Their decision is to change the mindset of the users by controlling the services they are using. Their OUTLOOK app (brought to the stores from Accompli acquisition) is the best email client by most reviewers and I’m one of them. Once they control the services they can control the direction to the backend in the mobility.

Samsung, Google and Apple are not small companies that cannot stop Microsoft from achieving its goals. But as Steve Jobs said once, there is always a horse running in Redmond!

The Power of BI

DIKW stands for data, information, knowledge and wisdom. Data is the raw output of the process. Once we put these data in a context, then it will be information. Information can be represented in a meaningful and useful way with the help of the historical experience and personal perception to be knowledge. Then what about the wisdom? Wisdom always can be answered with the why question? Why this decision not that decision should be considered. It is a reflection of the knowledge on the real action that always refer to future actions.

Then based on the above, what is the limitations of the business intelligence tools? Can the business intelligence tools reach to the wisdom and give the decision makers wise predictive decisions? I have worked with many BI tools (and I won’t mention any), the ultimate way for the current business intelligence tools is to build a mesh, complex and not normalized relationships between data to put them in context first and second thing to present them in sophisticated and correlated way.

What triggers me to write this article, is the evolution of two technologies. One of them is the Artificial Intelligence in bots, personal assistance, games and a lot of other applications. Second technology built on top of the artificial intelligence which is the machine learning. Machine learning depends on feeding the machine with more and more information to build some sophisticated relationships between them on spot to control the future decisions of the machine.

The prerequisite for all of these three technologies is the availability of data feeding source. I remember how TAY (twitter character created by Microsoft) learnt too quickly to be racist and pro-Nazism in less than 24 hours because people who chat with it taught TAY to be so in a very quick manner. Microsoft apologized for TAY attitude after that. In other words, the decisions taken by TAY weren’t wise-decisions according to the human cultural heritage.

All companies, researchers and universities are in the race to add the art angle to the science angle in the Artificial intelligence. The accounting is a science, but the economics is not, it is a combination of both science and art. You can build a BI tool to take decisions based on the accounting principles so easily, but it is too early to build a BI tool for economic decisions like wages-floor, rent-ceiling, interest rate, inflation throttling, budget deficit reduction and social security because the norms and social factors should be considered in such decisions. This is why Alan Greenspan served as chairman of the Federal Reserve for almost 20 years apart from the direction of the united states administration. The wisdom that we are seeking for is the ultimate goal and target.

I’m optimistic about the future of the business intelligence with the current advancements of its siblings, Artificial intelligence and machine learning. I’m optimistic that one day we can find a “safe” way to feed the machines with non-structured information reflects our norms, social life, principles and the most important thing is our customized measurements and understanding to the wisdom to get the wise decisions.