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Presenting effective analysis Incorporating analysis into business strategy
Utilizing Data Analysis Using analysis to bolster roadmaps Concentrating on results

Data Analysis, Market Analysis, Process Analysis, Performance Analysis, Product Analysis- the range of roles an analyst can perform are diverse; the objective is always the same, how can results be improved given the current state?
By and large companies hire analysts when times are tough or when a change is needed. The truth is companies can always benefit from sound analysis, but typically need some concrete reason to elicit said help.
Having worked with a number of analysts and studied the works of many more, thee are a slew of reasons for disconnect between clear findings and companies not incorporating valuable advice; it's that findings needed to be made clearer.
Proper analysis is not only using data analysis to support a position, but present real world situations to back up research.
Good analysis is finding trends, dominant factors, identifying the strongest benefits and most costly initiatives. Great analysis is getting a message across for a positive affect on business decisions.
Not everybody has the same respect for numbers or data analysis. In my experience, many decision makers will prefer to go with what they know, even if it conflicts with the numbers on a page. What's needed in situations such as that is great analysis, somebody to present analysis effectively.
What is presenting analysis effectively? It's being confident in the analysis in relation to the real world scenario, and then being able to relay that message to your audience. There is a stark difference between finding an accurate conclusion and then being able to get others to understand it. The numbers/findings are conclusions drawn from raw data, it's demonstrating how potential revenue is being left on the table by not capitalizing on certain proponents of the product; or perhaps not tapping into a certain market. The message should be, if you want to make more money, this is what you should do.
Many analysts fail to convince an audience because after delving into the numbers for so long, they become incapable of speaking English. Making your case is not about demonstrating your intelligence or prowess, it's about the most direct approach of getting a goal accomplished.
Great Analysis is taking your audience from Point A to Point B. Point A being the current state of affairs, and Point B is the improved state of events down the line with concrete steps laid out. To present data analysis without these steps is to fail in the role as an analyst.
In today's culture, analysis has enjoyed more widespread fame. From Fantasy Football and ESPN to Nate Silver outperforming the world and correctly predicting every 2012 US election result1Money CNN- Nate Silver Election Results, proper analysis has finally found the spotlight.
Why is it that while data analysis has been on the rise recently that analysts are not enjoying the limelight? Because while their findings may be precisely calculated, their message is muddled and void of consequence. People want simple, relevant information rather than to be bombarded with evidence. It's not always the easiest to explain analysis plainly, but that translation is an integral component of quality analysis.
Of course there are many different roles an analyst can fill, so each has their own methods for presenting analysis.
Business Analysis- By far the most ambiguous, yet common role. Burdened by subjective factors and ever changing conditions, Business Analysis is generally relegated to second rate advice. The truth is the field is underdeveloped, nobody joins because it doesn't get respect, and it doesn't get respect because nobody has joined to elevate the field. What could proper Business Analysis be good for? Perhaps to tell Microsoft to listen to consumers. An adequate analyst may present numbers of dwindling market shares to Microsoft. A good analyst would appeal to the CEO by telling vivid stories of Blackberry and HP, tying in links to current and past predicaments. By getting that message heard.
Data Analysis- Possibly the one which receives the most attention due to the money usually at stake, Data Analysis is the backbone of all Analysis. By nature numbers are not tied to language or perspective, they give an accurate account without bias or interpretation. So how can an analyst be held responsible for people listening to sound Data Analysis? Well simply put it's their job. Same as a business analyst, data analysis should present corresponding real world steps and instances to backup all figures.
Product Analysis- By far the most subjective field of analysis. Many good products have fallen wayside (Palm OS, Blackberry) while ridiculous concepts win public favor (think pet rock). How can Analysts be effective in such conditions? By adapting, find indicators anywhere and everywhere. Since Products are subjectively received by the public, they should not be analyzed objectively. Don't look at Windows 8 and say this is a solid system, it'll sell well based on past experience. Look at the current market and realize that past experience means exactly zilch; instead propose boldness when required. Interpret the market, understand consumers, and take it all into effect. Products should offer more than functional experience, a product should also take into consideration extrinsic values such as design and user time.
Process Analysis- The field least affected by current trends. Sure Google turned things on end with their 20% rule and breaking new ground by giving employees free reign, but business process remains mostly unchanged, sturdily rested on the foundation of hundreds of years of conventional business wisdom. Companies still need HR, vacation days, staff hierarchy, resource allocation, and sound employee policies. How can analysts adapt in a relatively unchanging field? By staying ahead of the curve and identifying the slightest edge wherever possible. The trends are there, in a stagnate economy companies can stay ahead of the curve by paying employees well, encouraging individual initiative, and investing wisely. Sure it's not required, but neither is success.
Market Analysis- The most finicky of all analysis, which is why they get the big bucks. Predicting economic performance is notoriously unreliable, there are countless new trends which can explode and turn the market on end at any time. Who expected Reality TV to become a dominate part the entertainment industry? Show's like MTV's Real World was on for more than a decade before ratings caught on. Now a majority of Prime Time programming is reality/competition shows. In the tech sector Smartphones turned the industry (the most successful in the world) entirely on end. How can anybody see any of this coming? Simple answer is that they cant and nobody ever has. Or at least completely But you can pick up on general principles. Cloud computing, mobile devices, open source products all point to general directions. We're entering a more consumer-centric era. Times are becoming more transparent as people become more informed inch by inch. Instead of reluctantly following course, why not prosper by being ahead of the trends? Sneak peak, the next step is predictive recommendations.
Performance Analysis- This field is where the most reluctance is found and therefore a more delicate approach is needed. No company wants to hear they're doing badly because the people in charge have their careers and paychecks on the line. How to deal with this? May sound silly but it's all about managing psyche. Don't tell people what they're doing wrong, but how they can get more mileage out of what they're doing right. No matter what you can always find aspects supporting that a company is on the right track. Even if past years performance having been lagging, pinpoint the one component which shows promise and concentrate on that. Veer them away from harmful promises by luring their concentration, instead of trying to pry them away from negative initiative, provide encouraging incentives towards new policies. It's not what you're doing wrong, it's what you can be doing better.
Great Analysis will present itself. While most people can be fooled by false information, there is no confusion when presented by the real thing. Understand the audience, dissect the data, and reassemble the information accordingly. Have a sandwich shop reluctant of idling customers? Dig up numbers supporting secondary business and a filled store. Tech company too concerned with proprietary tech and piracy? Show them Google's latest investor report.
In Greek Mythology, Cassandra was granted foresight but was punished that nobody would believe her. If she were a proper analyst she would have been able to boil all arguments down to their purest form and present iron-clad cases. Analysis should be bias-proof, disagreeing with the conclusions should be as difficult to contend with as the case for gravity.