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Part II: Analytics to Action….. The Holy Grail
Can-you-have-too-much-information?
… in my last blog we talked about reporting, BI and data mining, and ? the information overload. So how can help business users with solutions for better decision making, as opposed to drowning them in more data and pretty charts? That is the Holy Grail and the purpose of all this data!
Lets start by defining analytics. So, what is analytics? Neil Raden of Hired Brains, a market research and management-consulting firm, has said that, “the proper term for interacting with information at the speed of business, analyzing and discovering and following through with the appropriate action, is ‘analytics’. I agree. In the information age, this must be done by specialized applications built on analytics based on the requirements of the actions/recommendations required by a business function. Dumping data on a users lap with the message – “Figure it out!” is NOT analytics, and it not very useful either. (I am reproducing a picture I really like as it conveys the message so very well! The Picture is from mathewingram.com/work)
So – how can we transform the user experience for analytics? As mentioned earlier, this can only be accomplished by focusing the analytics on a business problem with the mission to deliver actionable tasks. The challenge is selecting a business problem that the analytics truly delivers unique capabilities and intelligence that is relevant to that problem. This level of focus can be perceived as very limiting, and hence many choose not to go this route. Why limit the scope of the analytics to one specialization, when we can claim that we can do everything! To that I say – you are better off doing one thing very well, as opposed to many with mediocrity at best.
I am going to bring this back to Emcien, as this is a company that has focused analytics on a very specific business problem. The problem is one of product variety, product variants, and lots of attribution. In this age of product variety, that is a problem that is causing tremendous challenges to various business functions.
The analytics automatically detects what features customers are buying, where you are making money. This SKU or configuration intelligence is leveraged for:
SKU Intelligence Analytics Used to Drive Application Specific Recommendation
- Better forecasting at the mix level - The application uses the analytics intelligence to determine the exact product mix with very high accuracy based on true demand sensing.
- Improving the customer experience at the point of sale - The application uses the analytics intelligence and guides the buyer to a good configuration based on the few features they have called out. And by the way – customers love it when you can recommend a configuration based on the few features they ask for. They want you to stop asking more questions and recommend a good choice.
While the analytics may throw out volumes of data, the user can relax, as he does not have to crawl through volumes of date wondering what it is telling him. Converting analytics to actions and recommendations minimizes human interpretation and error on a day-to-day basis. For analytics to be functional in business applications, this is a mandatory requirement in today’s business environment.
So – when you are evaluating BI tools, Analytics, Data mining….. what ever they are calling it! Ask yourself, how am I adding value to the company? What am I giving my business users? Am I adding more work to their busy schedule by piling on data on their computers???? If the answer is YES, please don’t do it. They will thank you for it.
If the data has not been converted to recommendations the business can act on, you will not get value from your investment!
Part I: Reporting, Business Intelligence, Data Mining, Analytics: Actionable Tasks!
Software vendors use so many big words and confuse customers. Our customers have often asked us to clarify – so here I go. The definitions in this article are based on research of these terms, and the collective opinion of many of our customers and prospects. Over numerous conversations with our customers and the discussions of the terminology, the clarifications always go back to the origin of the terms and then move on to change in usage. Hence this article folows that flow. I would love your feedback as it is important to help buyers understand this.
Business Reporting
Business Reporting, as the term suggests presents the data from the database in an easy to read format. This originated when business users were frustrated that all the data was locked up in databases. There was a lot of data, but no one could get access to it without calling on IT folks. Hence Business Reporting was born.
Business Intelligence
This is a fancy name for business reporting. Business intelligence (BI) is a broad category of technologies that allows for gathering, storing, accessing and analyzing data to help business users make better decisions. In a 1958 article, IBM researcher Hans Peter Luhn used the term business intelligence. He defined intelligence as: “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.”
In 1989 Howard Dresner (later a Gartner Group analyst) proposed Business Intelligence as an umbrella term to describe “concepts and methods to improve business decision-making by using fact-based support systems.” Then in the late 1990s the usage became widespread (Remember the Bubble!). Then. everything with any data reporting was called Business Intelligence. So today, Business Intelligence is a glorified term for “Business Reporting”.
Data mining
Simply put, Data mining is hitting the data with all mathematical methods available to a mathematician! The data source can be almost anything – news papers articles, financial reports, sales data, medical data, … . This means that the data can have structure or can be un-structured. And the mathematical methods that can be applied can include neural networks, genetic algorithms, statistics on steroid and anything else they can think of.
One may ask – why are they doing this? What are they mining? Well, the simple answer is that they are mining the data looking for patterns; any patterns that can reveal relationships. So the methods used are varied and the kinds of data that are mined can come from a myriad of sources.
The results of data mining are lots of data! In fact – the result of Business Reporting and BI has been data overload. Now that’s the bad news. In a world of information overload, the last thing that we need is more data. We have less time today than we have ever had before. Business users do not need more data. They need quick conclusions on what the data is saying, converted into actionable tasks. Simply put – “Please tell me what to do”.
… More on the discussion of analytics to action in the next blog.
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Variation is valuable
Advances in interconnection technologies are driving an increasingly demand-driven market. Customers are learning to expect to get what they want, when they want it, how they want it. And they tell you in each and every interaction they have with your company, or not. In a demand-driven world, increasing product variation and complexity in your business model is inevitable. Left untended, your business can become a tangled web of counterproductive business strategies with a dense portfolio of product families comprising thousands, even millions, of variants.
However, make no mistake, variation is valuable. To deny complexity or view the long tail of product variation as a management failure is to deny diversity of the world in which we make our living. Eliminate complexity in your product offer and you will find yourself competing with boatloads of product from China, India or any of a number of low-wage production markets.
The “keep it simple” principle is the root of good management. However, as Oliver Wendell Holmes, Jr. has observed, “I would not give a fig for the simplicity this side of complexity, but I would give my life for the simplicity on the other side of complexity,” it matters which form of simplicity you choose. The wrong simple answer is to try to focus on the 20% of product variants that make up 80% of your revenue, the head of the ubiquitous Pareto distribution, and find ways to minimize or eliminate the so-called unprofitable remaining 80% of product variants that lurk in the tail. Hello commodity, goodbye margins. The right simple answer is to deliver Intelligent Variation based on the voice of the customer shouting through the many interactions they have with you each and every day.
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