Wednesday, January 19, 2011
Business intelligence or BI refers to skills, processes, technologies, applications and practices used to support business decision-making.
Several factors are analyzed in the process of making high quality decisions. Customers, competitors, business partners, economic environment and forecasts, and internal operations data all play a part in the business intelligence dynamic.
Customers: By collecting customer data, either (POS) Point-of-Sale or surveys and polls owners and managers can use this data to make important business decisions in marketing, budgeting, inventory, demographic targeting, and much more.
Competition: Competitive analysis can help your business in two major ways. First, by analyzing your competitors, you can take the very best of their ideas, and if you're not doing them, add them to your business mix. In addition, knowing each competitor well, allows you to look for areas where you can make your business stand out from them.
Partners: Making sure to use a careful selection process in selecting partners, and that all of your partners deliver on a timely, professional basis and offer affordable prices are keys to making your business run smoothly. Your business is only as good as the company it keeps, so make sure careful pro-active analysis and ongoing assessment is done on partner performance and consistency.
Environment: The economic landscape and especially that of your own particular industry are very important areas of business intelligence to focus on. By analyzing the economic climate, and making your business flexible enough to change with the times to keep up, you can use business intelligence to stay ahead of your competitors who are not keeping up-to-date.
Internal Analysis: Internally, you should analyze your businesses weaknesses and strengths often.Assets, liabilities, credits and debits also need regularly monitoring. (KPI) Key Performance Indicators are one of the most common ways businesses today measure their progress. KPI analysis can be done on a daily, weekly, monthly, quarterly, bi-annual, or yearly basis. Business intelligence can help you decide which schedule is right for your company. KPI gives businesses a way of analyzing data, and forming strategies based on that analysis.
Many businesses use outside IT consultants to help them develop a "digital dashboard" to monitor all of their business intelligence data from one central focus point. An outside IT expert can help you design and carry out a network approach, where all BI technologies are able to community with each other, both inside and outside the business. Companies need assurance that they have a sound business intelligence infrastructure in place first, though. A business intelligence consultant can also help your business with this step.
Without a good BI plan, you are doing business in an information vacuum. It is a crucial part of starting, operating and preparing your business for changes. In the years to come, it is those businesses that outwit their competitors through flexibility, competitive analysis, and quick retrieval of crucial data that will stand the test of time.
An integrated set of software and hardware that is designed to meet a specific use is what constitutes a data warehouse appliance. This generally is made up of many servers, data storage devices, operating systems etc being very affordable and effective has emerged as a vital part of the data warehousing market. This appliance can be used to optimize different areas of data processing. Many appliances use languages like the SQL for interacting with the appliance on a database request level. Generally a true appliance requires no indexing or fine tuning and like other ordinary household devices is very easy to use and maintain. This makes it possible to set up a big data center warehouse in just a short span of time.
A data warehouse tool draws power from Massive Parallel Processing nodes and can deploy countless query processing nodes in a single appliance package. An appliance is capable of giving performance advantage that is practically a hundred times faster than general-use data warehouses. This amounts to low costs and low maintenance and automatically lesser power and cooling requirements since processors are not made to handle voluminous data. Data warehouse appliances are advantageous because they allow big companies to staff their warehouses better and help smaller organizations to resolve business challenges. Data center warehouse is therefore largely responsible for the manner in which businesses operate today.
Business intelligence implies activities that a company undertakes to get data about their competitors covering areas like market analysis, industry analysis and competition analysis. Even industrial espionage, it is believed, is a part of business intelligence. Here either an organization hires an outside agency or builds its own intelligence group to get inside information about the company's performance and areas that need improvement. It may then go through records of other businesses in the same field and customer surveys and at times also employ a spy to discreetly gather data. Unlike classic information gathering techniques, business intelligence systems make use of advanced technologies in data mining. Here all segments are interconnected and help to inform each other about their insights to get the complete picture. Business agility grows with business intelligence allowing an organization to exploit constantly changing market conditions.
Business intelligence in Australia is highly developed with the country ranking amongst the top five IT nations in the world. It can boast of good broadband connectivity, great internet security and strong government backing. It services are found to be taking control over nearly all spheres of the economy here ranging from social services and education to business, engineering projects to media and computing applications.
Characterize the Environment
The following list outlines the items and issues to cover in attempting to characterize the environment within which your challenge is encapsulated.
- Characterize the Environment
- Organizational Scope
- Project Sponsorship
- Business Context
- Business Objectives
- Current Data Landscape
- Solution Objectives
- Technical Environment
The topics outlined above may not all be necessary for some smaller organizations and in any case, it is not recommended to take a heavy approach to most of these items. All that is required is that they be given some thought and be documented if there is any useful information to be captured.
It may be that you are launching a BI initiative that is intended to eventually serve the entire organization. Titles like 'Enterprise Data Warehouse' (EDW) and 'Corporate Information Factory' (CIF) have frequently been given to such initiatives.
On the other hand, it may be that only a subset of your organization is the intended user and customer of the product. A division of your company, or possibly even a single department.
An all-too-common practice has been the creation of Data Marts an a virtually ad-hoc basis, resulting in an unknown and uncontrolled proliferation of such entities. It was recently published that Hewlett Packard launched an offensive against such a proliferation when it was discovered that there were more than 750 Data Marts in existence across the organization. This is when Business Intelligence could start to lose its true intended purpose.
Capturing the details of the organizational scope of your BI Initiative will serve to define the limits of the project.
Any project needs to have its sponsors well defined. It is a good strategy to encourage a vibrant relationship between the sponsors and the delivery team. Record who they are and work on that relationship. If you are the sponsor then be prepared to maintain close contact and involvement with the person or team implementing your BI solution.
Within the organization that is sponsoring or requesting a BI facility, there may any number of business processes, databases, application systems and sub-organizations. Take time to make a record of those for which the solution is to relevant, either as data sources or expected areas of enhancement.
Why do we need a BI solution? Someone in the organization came to the conclusion that this would be beneficial. Someone is aware that the solution will meet one or more needs. What are those needs? What does that person or group expect to achieve? In what way will their aspirations be met? They must have a reason, or many reasons, perhaps for going ahead. Those reasons will indicate and help crystallize the objectives of the BI Initiative.
Current Data Landscape
Now that we have organizational scope, project sponsors, a business context and objectives, we should try to define the data sources that need to be leveraged in order to provide the candidate information from which some intelligent business decisions can be derived.
At this level it is sufficient to speak of this in terms of databases or applications or functional areas covered by an application.
Additional information about the data sources should be collected. How easy will it be to learn about the data source? Is it well documented? Are there still people available who developed, maintained or supported the database that can contribute inside knowledge? Is the source 'out-of-bounds'? Can we only obtain data from it under some constraint, such as time, frequency, security policy, etc.?
The information gathered so far will help direct your efforts and maintain control over scope, cost and delivery aspects of the project. They may not, however, define everything we might be able to learn about the nature of the target solution. It is possible that corporate or IT policy may also impact the size and scope of the project.
It is possible that technical limitations exist or resource availability limitations exist. There may even be limits on funding that prevent all the business objectives from being pursued all at once.
Sometimes, it makes sense to extend the scope a little because the effort of visiting one or more data sources just to obtain the requested data me be wasting an opportunity to pull more useful (but not yet requested) data, This is a very important consideration because returning to the same source later is far more expensive than picking up data now that may even be in adjacent columns to that which we have come looking for. This is one area where an experienced Dimensional Modeler is able to point to 'easy gains' that could soon satisfy a growing appetite for analytic data.
It will be much easier to estimate the size of the project if we know something about the challenges it may present. One such challenge is dealing with the issues surrounding the way the data is currently hosted. Is it all in the same kind of database? Is it all in the same location? Are there common standards in place governing naming conventions, data type usage, data structure designs, etc?
Data is not always sitting in a database, nor is it always easily accessible. Sometimes it is necessary to access data that has already been extracted from its original source and stored somewhere else. It may be necessary to reuse the data feed of such a transfer of data from the destination. This can introduce serious issues of data reliability and stability. if the second destination has itself transformed the data or if the data has been summarized to a higher level of granularity or even stored as a periodic snapshot instead of at an atomic level, there will be issues.
Besides the need for resources on the BI project, there is often the need to call on the help of others outside the project. The lack of such resources, or limitations on their availability can cause problems for the BI Initiative.
Large companies tend to be able to fund large projects. Conversely, small companies cannot. However, outside of this fact, there is a need to consider whether a large project is actually the most effective approach to BI. Many initiatives have come to grief because the challenges involved, compounded by the inherent difficulty of coordinating large scale projects, leading to massive over-runs and wasted time.
One of the key areas for devastating misjudgments is that in which organizations inexperienced in DW and BI take on projects that are too large and too complex for their relatively inexperienced team.
Regardless of whether funding is easily obtained or not, it is strongly recommended that some kind of 'pilot project' be initiated first, to gain experience and confidence in dealing with the new technologies involved. Then after an initial smaller success, the team (or individual, as is often the case) can move on to take more territory.
Key to success is knowing how much to attempt rather than how much to fund.
Establish a Roadmap
The mode under which the BI Initiative will be conducted is the most important consideration at the start of the project.
Historically, most software application development projects followed a phased plan that was essentially serial in nature. Often referred to as 'waterfall model' processes, these were so named because the product of the first phase 'poured' into the second phase, the second into the third and so on, regardless of the name or purpose of each phase.
Eventually, it became obvious that this approach could be responsible for many of the ills that plagued such projects. The fact that any given phase is dependent entirely on the quality, appropriateness and timeliness of the products of its predecessor meant that any single phase had the potential of setting the limit on the overall project success, of being the weakest link.
Furthermore, the very act of feeding one phase with the documented results of another could introduce defects due to the misunderstandings, ambiguities, lack of clarity, etc., resulting from this form of communication. Surprisingly, the creators of one phase's deliverable were often not available for consultation with the recipients of their efforts in the next phase. Many weaker processes did not mandate a review (or quality gate) at the end of each phase.
Yet another issue with Waterfall models is that the project is not finished until all phases are complete. As this could extend into years, it would be necessary to 'freeze' requirements until the project was complete. Business changes would have to go unattended to because interrupting this process was too disruptive to be tolerated. Also, any error in delivering against the original requirements may not come to light until the very end of the string of phases, when it is then the most expensive to repair.
Evolving the Solution
Avoiding all the above issues is not a trivial task. Splitting the project into 'waves' is sometimes attempted to reduce the work going through the sequence of phases and therefore reducing the time frame of each wave is one, often used approach for very large projects. However, this does not remove the problem-causing imperfections of waterfall models, only 'divides' in order to 'conquer' them.
The approach that often produces the most successful result is that of 'Iterative' development, or prototyping. The main aim in this method is to work as quickly as possible toward a reduced end-product but one which can still be used, or at least, demonstrated.
Its advantages are: a quicker end point at which the product can be evaluated; an opportunity to learn from mistakes, misunderstandings or unseen challenges and the availability of a version of the solution that the sponsors can try out to see if their ideas were sound or in need of refinement. Indeed, the all-round learning process afforded by the first iteration is one of the strongest arguments for the approach. This takes us away from the need to 'get everything absolutely correct, at the first and only attempt.
The virtual impossibility of such an outcome with the waterfall model is certainly what leads to the creation of a 'Phase II' on most projects. Phase II may include new features but it usually includes a lot more in the way of 'rework' of the initial release.
Establishing a road-map for the project involves the decision to use the appropriate style of process and determining what to deliver by way of a prototype.
Dividing the project into two or more iterations offers many advantages if that option is available.
..to be continued in Part Three of 'How do I Implement Business Intelligence?'.
MeasureGroup™ co-founder, president and CEO, Derek A. Ashton is a career professional with more than forty years of IT experience. He was the designer of the world's first ATM for TSB Bank (now Lloyds). Mr. Ashton has been a speaker to audiences at major venues on Software Process Improvement and worked directly on all of the company's Data Warehouse assignments, either in a leadership role or as the DW Architect.The products offered by MeasureGroup™ are actually the result of developments made by the company, to r
What you don't know will hurt you Imagine you're the owner of a successful wholesale company that's been growing really fast. Large and small retailers are beating a path to your door to buy your product. Things are looking great. You've predicted sales are going to grow by 50%, so you plan purchases of your supplies accordingly.
All of a sudden, a year goes by, you don't have any cash to pay next month's payroll and your warehouse is full of unsold items. This situation hits you like a ton of bricks, from left field (sorry, I can't think of anymore clichés to add to these two). What happened? You didn't realize that while sales were only growing 20%, your inventory was growing by 50%. You lost track of your numbers. A situation similar to this happened to a client of our friend Ken Kaufman of CFOWise.
Situations like this happen to hard-working entrepreneurs throughout the world. It's probably happened with your business, your labor of love. You've busted your tail to build your company from scratch. You've worked 10-15 hour days, surviving literally on fumes. Your company has gotten to where it is today based purely on the strengh of your will and your vision for the future.
But now that you've reached a certain level of success, you've plateaued. Cash flow and profitability still seem elusive. Customer service calls are on the increase. Your inventory is stacking up. Your kids are wondering when they'll be able to take that big vacation to Costa Rica you've been promising them "when we're successful." But you're still working as hard as ever.
The problem is, things are moving so fast that you don't know the basic numbers of your company. Despite the warnings from your accountant, you can't find the time to sit down and really figure out what the numbers are telling you. You've got another proposal to write, a negotiation with a new vendor, and a new marketing campaign to kick off. That's where Business Intelligence comes in.
You can't improve what you can't measure: the case for Business Intelligence The entrepreneur's dilemma is that the skills that got you where you are today are not the skills that will help you grow into a viable, sustainable business that doesn't need the "indispensable you" to operate it on a day-to-day basis.
What helped get you where you are today is your passion, hard work, salesmanship, marketing savvy and unshakable vision for your business, yourself and your family. What will help turn you into the next Inc. 500 company is to know what the numbers are on every aspect of your business so you can stop bad habits, improve good habits and institute new habits for growth. These numbers have to be at your and your employees' fingertips at all times. They've got to become part of your company culture.
Basic numbers such as:
Track revenue, cost of sales, gross profit, gross margin, revenue trends, sales per sales executive, top 10 products, sales by region, sales per customer, etc.
Track payroll, utilities, travel, actual expenses vs. budgeted expenses, expense trend analyses, expenses by cost center, expenses by type, etc.
Track inventory days left, inventory by product, fastest moving inventory items, slowest moving inventory items, overstocked items, etc.
4. Accounts receivable.
Track expected payment schedule, fast pays, slow pays, payment trends, etc.
5. Accounts payable.
Track past due payments, categorize vendors by payment terms, check payable trends, determine who to pay first and who you can delay payments to, etc.
6. CRM data.
Track details on sales reps, best customers, worst customers, customer complaints, customer loyalty, defections, referrals, etc.
7. Human resources.
Track vacation days, employee efficiency, employee complaints, employee retention, compliance, etc.
This is by no means a comprehensive list. Here are more things that you can track in order to grow:
- Technical support calls: time to resolution, issue tracking, common complaints, favorite features.
- Route driver efficiency: miles driven, time taken for delivery, time per customer visit, on-site invoicing.
- Product optimization: most popular products, least popular products, most profitable products, least profitable, product returns
- In-store sales: most profitable days of the week, most popular specials, least effective specials, most effective point-of-purchase displays
- Logistics: best delivery companies, slowest delivery companies, number of lost items during shipping, number of broken items
- Medical: most expensive procedures, most profitable procedures, most complicated procedures, procedures requiring minimal skill
- Software development: developers producing most bugs, most efficient developers, best development environments
- *insert your urgent items needing measurement here*
Keeping it simple Have we lost you yet? Still here? Good. Now you know what you need to know to take your company to the next level.
But the big question is: who has time to analyze all this? Who has time to organize all these numbers into spreadsheets and try to figure out the best way to organize the data? Your accountant? Maybe...
What about a simple-to-use Business Intelligence tool?
The terms dashboards and analytics are often cavalierly tossed around as terms associated with Business Intelligence, but here for the first time a brief explanation:
Dashboards are tools to visually display data such as Performance Indicators and Key Performance Indicators via tables, charts, graphs, etc. Dashboards allow you to customize what is displayed or you can build them from scratch with the information you want to see. Dashboards also allow you to "drill-down" into the data, such as viewing revenue by region, department, product, and sales executives, for example.
Analytics is the practice of looking at historical data to gain insight and understand business performance. Through analytical capabilities, users can dissect business data to fully understand and answer the "how", "what", and "when" questions. You can in turn use this data to plan the best performing mix of products and special offers, for example, and predict with accuracy what the outcome will be.
Sounds complicated, right?
Here's the beauty of dashboards and analytics: they're now available in pre-built, easy to use visual displays. With simple point and clicks, you and your employees can actually see how your products or expenses are trending.
Click on certain interesting metrics to drill down and find out: which customers are really slow pays? Who are my top 5 hot-shot sales guys? What was my best retail sales day and why? What was the actual product that sold the most that day?
You want to see how things are different now than they were, say, 3 months ago? View a visual time-line to see how your expenses or inventory figures are trending. Want to urgently correct something that you didn't know was going downhill, fast? Start a project with your BI tool that will shoot off emails to your people to take immediate corrective action.
How to get the info into the tool Ok great, now I can see all my company's data visually, and it doesn't take a rocket scientist to figure out how to understand the numbers. I can see where I'm bleeding red ink and I can take action (you like taking action more than you like crunching numbers).
But how do all those numbers get there?
Glad you asked.
Most BI solutions today have simple tools to help you with that. There are Extract, Transform and Load (ETL) tools that can connect directly to your accounting system or CRM, providing a tunnel for your info to get from one place to another on a scheduled or manual basis. There are also excel templates so that when you export the information from your accounting system you can organize them into the right columns with the right column headers and then upload them into your BI tool.
It wasn't always that way. As little as 3-4 years ago these kinds of tasks required highly paid data analysts who were experts in databases, data integration tools, and DTS scripts to get the data from point A to point B. As a matter of fact, it used to require these gurus to build the reports and dashboards you needed to actually see the data that would be useful to you. Ugh!
You're actually lucky you're in business now. A lot of blood, sweat and tears have been shed to make these tools easy for small and growing businesses to use, and affordable. Cost of BI tools Sounds expensive, doesn't it? Well yes, it was.
Traditionally BI tools were reserved for the Fortune 500 and just below. They really needed tools to keep their upward growth trajectory (and some of them didn't do a very good job. Maybe they spent too much on their BI solution???). They were complex, the tools were expensive and unwieldy, and the implementation took a long time and sometimes cost more than the tools.
But now BI applications are essentially websites. You use websites to run your business. If you use Google Analytics, then you're using the simplest, most commonly used BI tool delivered on a Software as a Service (SaaS) model. SaaS really means software that's a website.
The advantage of using BI tools, or any software for that matter, delivered as a SaaS, is that the cost can be broken down into easy to consume monthly payments. All the maintenance costs and hosting are absorbed by the software vendor. Literally for the daily price of a Latté you can have access to a web-delivered, powerful tool so you can measure all your company's key numbers and get a handle on your business. You can focus on growth, and empower your employees to check on important company metrics and take corrective action if necessary.
So you thought the beginning and end of BI is the setting up of a cutting edge Data Warehouse? Well, think again. The BI landscape has undergone a sea change. Trying to articulate its various aspects and how it is evolving would fill several books. In this article, we will skim the surface and talk about the various ways in which BI is being perceived and handled in the current IT landscape.
If Traditional BI = Data Warehouse + Reporting Tools
BI 2.0 = (Past + Present) Data/Analytics + Future Business Analytics + Reporting Tools
I have used this simple equation by way of demonstration: BI v2.0 is all about studying and analyzing Past, Present and Future trends using archived and real-time data feeds and then turning this data into knowledge for stronger decision-making.
It is real-time or it is of no real use:
When it comes to Traditional BI tools, the data retrieved from them, in today's parlance, is considered outdated. Intelligence is gleaned after the fact-after significant time has elapsed between the actual activity and the time when it is analyzed in either an individual or aggregated fashion. In this Internet Age, even the lapse of a day could render that data obsolete.
BAM and CEP are real-time tools; data is analyzed as the transactions are being executed. It is this optimally effective decision-making in the moment that makes BI 2.0 so attractive to new age businesses.
Let us now look at a common use case: the Shopping Cart. Shopping on the web is one of the most common online transactional activities today, and it is increasing year over year. For high traffic sites like eBay and Amazon, business cannot be made truly agile without the use of real-time analytics. Traditional BI just will not suffice.
So let us consider the following example:
• Acme Mart is a medium-sized discount store with brick and mortar stores throughout the country.
• It also sells merchandise through its high traffic website acmediscountstore.com.
• The transaction volumes both at the stores and online is quite large-to the extent of several million per day.
• It has a mature, established SOA infrastructure and its entire order management process is service-enabled.
Acme Mart also uses BAM (Business Activity Monitoring) to monitor services. Custom dashboards have been built to monitor sales of specific item categories and even items through sophisticated dashboards.
Contrast this with a similar business that uses Traditional BI mechanisms. It is obvious that it will not be able to match the level of agility of Acme Mart. By the time the sales data is analyzed, the opportunity to respond proactively has passed. Acme Mart is clearly more capable of reducing costs and increasing revenues via its real-time BAM-enabled BI solutions.
While CEP (Complex Event Processing) is similar to BAM, it is more of a services agnostic technology. It is sort of a real-time message aggregator that can process messages from various different sources including web services. One example of this can be applied to the current use case, along with order information, if related stock price information for the companies that produce those products are also needed in a separate dashboard then this feed that would normally come from the likes of a Bloomberg or Reuters can be combined with this Order data and displayed.
BI Technology Trends: The Past
We need not go into the details of how BI functions were being performed or are still being approached using DW-driven technology. If Business needed insights into key trends then they would follow this well beaten path:
- Setup a de-normalized DW or Data Mart
- ETL information from transactional data stores into DW
- Use reporting tools like Cognos to generate the required MIS reports.
Therefore, this was the tried and trusted method and was considered business as usual. Traditional BI is very batch-oriented in nature and not real-time. However, while real-time mechanisms may look very compelling in terms of their value proposition and ROI, it may not be feasible to implement these quickly as they are dependent on a services-based infrastructure.
BI Technology Trends: The Present
As the competitive landscape becomes more intense, the need for real-time business intelligence is almost De Rigueur in certain types of industries, in order to gain business agility and competitive advantage. With the advent of technologies such as BAM and CEP, it is possible to perform real-time and even future what if business analytics.
BAM and CEP fall under a new category called Event Driven Architecture (EDA). These tools permit BI in both synchronous and asynchronous modes.
Business Activity Monitoring (BAM) is associated mainly with Web Services. It is a dashboard driven toolset that is comprised of various design time components and a runtime component. It is used in conjunction with other runtime components of a typical SOA implementation, such as ESBs and BPEL engines.
CEP (Complex Event Processing) is similar to BAM with the difference that CEP is not tied to web services alone and is message agnostic. You can aggregate disparate messages from myriad sources and use them as part of one CEP application.CEP is usually event driven.
To keep the cost of delivering goods and services in line, companies must find ways to reduce waste and eliminate inefficiencies. You can lose control of your cost structure putting pressure on your gross margins without proper infrastructure. Restricted cash flows are forcing companies to analyze cost structures by delving into available information at their fingertips. They need to be sure their fingertips are able to touch the required information to make good business decisions. Are your fingertips in the pot?
Analysts point to a rising interest in business intelligence software. An integrated business intelligence solution that generates accurate and timely data puts you in a position to identify and quickly address inefficiencies. Dashboards can deliver immediate feedback. Use analytics to monitor operational defects, maintenance costs, general procedure inefficiencies, and then track progress to measure the baseline against future costs. You will need the ability to further investigate costs, seek areas to optimize systems and processes. Even if your gross margins are better than average, expenses may be high. Follow the leading companies that carefully manage expenses to deliver a consistent cash flow.
In today's business environment, an organization needs to address all outstanding issues, but you must first identify and prioritize existing problems and then focus your time & energy on the most crucial ones. No organization wants to wait until a department is significantly over budget before taking action. However, if you manually track project or program status, you risk not only wasting time and money on an ineffective approach, but also delay your ability to identify and then correct problems. All of these considerations continually confirm the need for consideration in technology investments. Streamline processes, reduce headcount in selective areas and invest in systems and infrastructure to improve customer management or market intelligence.
Business intelligence solutions help you identify issues that fall outside the norm and spot potential problems by generating timely and accurate business data. Once you identify the root cause of a problem, you can take corrective decision. These solutions help you monitor and track results and also alert if problems reappear.
A solution that enhances performance both at individual and the corporate level, supporting greater alignment and accountability is very much needed for any business to succeed. Transparent and integrated software solutions make employees trust the data, help them understand the importance of their daily actions and their affect on the business goals. By clearly mentioning their responsibility towards the goals and timelines, you can communicate explicit performance expectations among all the employees.
Dashboards integrated with software such as Microsoft office that you use everyday help you communicate metrics, track progress, and reward success. Dashboards give the immediate performance feedback; you get the information you need to take quick and decisive actions to correct behaviors, rather than having to wait for quarterly reports to decipher trends. Visualization tools help your employees and you focus quickly on high-impact issues. Your entire team can see where data comes from and how results are calculated and can interact with reports, instilling confidence in the numbers and encouraging individual and collaborative efforts that benefit the company
Tough economic conditions require companies to go beyond slashing costs. You need to build an efficient and high-performance organization based on a strong foundation of information. Take a global view of critical information to move from just reacting to economic pressures to making the most of your business information. Do you have the proper software tools and place to give you the dashboards, the depth of information, reporting, and analysis for proper direction of your company? A careful review of all of your software vendors and information providers will provide you with those answers. A general housecleaning and analysis of overall procedures should be conducted annually, with an in-depth analysis every other year. Fastrac Companies like Facebook and Social media, Amazon and shopping online, Google and Internet, companies that lead the pack are there for your assistance. Take a hard look at the wealth of information available to keep you on top of the game.
So why is Saas BI so suitable for smaller businesses?
1) Small and medium-sized businesses often cannot justify the large CapEx of traditional BI, do not have the IT resources to run an on premise database and server system and are not sure that they have the breadth or depth of data to warrant such a system. Often their needs change and evolve far faster than software is developed and installed. SaaS payment structures mean that you have no CapEx and only pay for the amount you use the product. If half your users find they they aren't deriving any value from the software, they can easily cancel their subscriptions at the end of the month, halving the cost.
2) Traditional BI demands technical expertise both to manage and use. Business users could not quickly perform analysis themselves; queries had to be made through the IT department and often involved long delays. As there is no software to install, there is no daily maintenance or routine tasks to be done, so nothing to require extra IT hands or expertise. This frees IT professionals to concentrate on strategic IT and growing the business.
3) With traditional BI having enough data to justify the BI spend is certainly a problem. The huge upfront costs and time investment often cannot be justified by the need for a couple of key decision makers to analyze a small number of records. SaaS BI gets rid of this problem as it provides fully functional BI suite available for just one person. SaaS applications can be rapidly scaled up or down as your business needs change.
4) Most SaaS products are lightweight and designed to complement the investment in data storage and manipulation that you already have. For example, most SaaS BI solutions plug directly in to online and traditional sources to extract data, then allows creation of visualizations and dashboards with a few clicks.
5) Access and sharing were the original drivers of the SaaS cloud computing model so applications make it easy to get useful visualizations to the right people quickly by inviting people to your dashboard's URL or embedding it in a website or blog.
BI products have traditionally required huge upfront costs, had long lead times and demanded technical expertise to use. SaaS allows powerful functionality without the need for any of these, making it a highly profitable investment for SMBs. This isn't to say that large enterprises cannot benefit from SaaS BI too. Within departments or teams, larger organizations are deploying SaaS BI more and more as they realize its potential.
OLAP is that piece of the tool set that provides Dimensional Analysis, enabling huge volumes of data to be efficiently made available for exploration in a large variety of formats and arrangements.
The repository of high-volume data and the special methods for designing its storage was given the title of "Data Warehousing" (DW). Within the DW, a representation technique called "Dimensional Modeling" evolved, which is aimed at economic, context-based access (querying) of the immense tables held in the DW database.
Once the data has been captured and arranged in this way, through a process known as "Extract, Transformation and Load" (ETL), it can be passed through a further stage of processing that generates a "Cube".
The Cube, in this context is actually another highly optimized form of storage in which the Dimensionally Modelled data can be pre-aggregated and cross-mapped for efficient retrieval and presentation to the user, who can enjoy parsing data at many levels of summarization moving quickly between almost limitless varieties of analysis.
Activities such as setting up multi-dimensional charts of data summary (known as "slicing and dicing") or moving to lower levels of detail and back again to highly summarized versions (known as drill-down and drill-up), using tools to create graphical representations of the Cube data, with a great many formats from which to choose.
Employing yet other tools to perform sophisticated analyses, whereby trends and anomalies buried deep in the data may be discovered, understood and exploited (a technique called "Data Mining"). Data Mining models are created and refined to become sensitive to and resonant with the data patterns and can themselves be used to generate forecasts of future trends and movements within the tracked data. A veritable gold mine of such gems lies hidden and largely unexplored in the "exploding" mountains of data that have accumulated in companies since the price of storage came tumbling down.
It seems that IT organizations have been hanging onto data, keeping it in cold-storage, knowing that there will come a time when it will be of benefit. This is analogous to the hopefuls who upon departing this world, have their brain frozen, awaiting the emergence of technologies that can bring it back to life, perhaps with an artificial body. Business Intelligence is the technology that allows companies to unfreeze their data assets, bringing them back to a much more useful life than before. A New Era for Information Usage?
Early in the eighteenth century, inventors were making new discoveries about heat, energy and motion. There quickly evolved coal-fired, steam-driven locomotion (railways) and pumping engines (for the mines) and giant power plants for making every machine in a factory turn and churn incessantly. Spinning cotton, weaving cloth, cutting and shaping iron and then steel. The Industrial Revolution was born. Mills and factories sprung up all across the coal-rich fields of Northern England (this writer's birthplace - although a little later).
From their long heritage of back-breaking land work, people seeking to earn a regular (monetary) income flocked to grasp the many new (but equally back-breaking) factory jobs that emanated from the urban sprawl of gleaming red-bricked labyrinths, that housed these awesome machines. Industrial empires were spawning all over and wealthy (already) magnates-to-be, stepped up to invest, build and rule over them.
What did they think of Business Intelligence? Of course, it seems unlikely that the term would ever have been uttered back then but, business empires had to managed somehow. If you could see those monolithic structures and enjoy the experience of visiting them, still churning and clunking, you may notice that almost every square foot of factory space was given over to production or storage of raw materials and finished goods. No room for desks and filing cabinets and, of course, no information technology; not even a telephone!
In one corner of the giant mill, you will see a well appointed office (where the owner would be found most of the time) and one or two nearby, less auspicious areas, being the workplaces of a couple of clerks, whose job was to record all the transactions of the business. Keepers of great leather-bound volumes of hand-written fiscal matters, committed to parchment but rarely revisited. So where was the "Decision Support System"? Where were the "Executive Information Systems" and "Balanced Score Cards"?
It was all there; all that was needed in those horse-drawn days, where real business took place between the various well-heeled mill owners over a mug of coffee or a mulled ale at some local tavern, gentlemen's club or city-based mercantile gathering hall. The mill owner was kept informed of the production issues, inside his work-house, by visits from the foreman and kept his business knowledge up to scratch by his time spent over the tablecloths of his privileged meeting places. Intelligence was handled by "word of mouth". Business deals were a handshake, followed by a letter, days or weeks later.
After the initial gold rush of mechanization, little changed for a long time; at least in terms of administration methods. Only after a slow but gradual increase in the number of non-production workers and the (mostly) record-keeping tasks they performed, would another unannounced "giant leap forward" occur, to irreversibly revamp the business scene once again.
Hail, Data Processing Due to regulatory requirements, statutory accounting practices and other external demands, together with a burgeoning management's appetite for information, the ever-growing office spaces were becoming jammed with bursting-at-the- seems filing cabinets, filled with all manner of records of the company's actions, transactions and anything else that mattered. All typed-in-triplicate, carbon-copied and filed in strict order (ready to be retrieved and hand-altered or joined by an extension or superseding entry.
Hot, clattering, manufacturing machinery had ushered in the Industrial Age and hot, clattering data processing machinery would now usher in the Information Age. Tabulators, card punches, paper-tape punches and prattling line printers were among the first commercially successful data processing machines. Rapidly progressing into electronic mainframe computers, humming, or even whistling musically (but still quite hot) and requiring huge rooms for their banks of hand-threaded core-memories (as much as 8 Kilobytes per cabinet), and looms of backplane wiring to connect central processor's thousands of discreet components, soldered to hundreds of Bakelite circuit boards.
Strangely, this great revolution of number-crunching, heat-belching behemoths did little to shake up the world of business. Large corporations would quickly shell out millions for their first pride-and-joy, accompanied by the odd educational institution, here and there. However, vast swathes of less well endowed organizations held back, presumably seeing no threat of extinction as the consequence of not joining in the party for the second great era of industrialization.
Well maybe it is not so strange. The astute leaders of small to medium sized businesses (SMB's) not known for "leaping before they look", should be expected to play wall-flower, at least until the proposition looks sound, justifiable and absolutely necessary for survival. Today though, a mere sixty years on, it is hard to find any kind of business, of any shape, size or ethical standing, that does not have heavenly amounts of computing power, at every fingertip.
Bigger, faster, cheaper, more. So the years went by at the "speed of thought", everyone got onboard and computer systems became as common in the workplace as steam-pipe
leaks, machinery-induced deafness and finger blisters had become in the cotton mill.
Actually, the "Technology" part of "Information Technology" (the "T" in IT) has come an incredibly long way since the days of machines peering through holes in cardboard (which, incidentally, was first conceived of by Industrial Revolution luminary, Jacquard, the inventor of the all-important weaving loom that bears his name).
Some software of today is also astronomically more advanced than that of the mid-twentieth century. Lamentably, it is, however, the "I" in IT that has not kept pace with the advances of electronics and related cost-performance ratios.
With some exceptions, corporate use of computers has essentially become locked into the business of record keeping; frozen solid in the first great ice-age of non-progressive wheel-spinning, running faster to stand still, quagmire, where huge budgets evaporate, just trying to keep up with the avalanche of necessary upgrades and replacements.
Is that the Cavalry I hear?
Having painted a grim picture of stagnation and nil return on investment, we have paved the way for the trumpeters and knights in shining armor. So the cost of storage has come down dramatically, the data we are holding there has ballooned dramatically, now must be the time to do something with it, dramatically.
Instead of just "record keeping", let's use all this computing power and endless data in ways that can make us better at what we do. How about introducing software that performs large-scale, sophisticated analysis. How about using that sophisticated analysis to help us make better decisions. How about using improved decision making to choose a better direction to go in and better direction to improve marketing efforts, customer experience, product investment, vendor selection, volume prediction, price setting, etc.
Let's just call this whole new leap forward "Business Intelligence".
Get more intelligent about business by seeing more clearly what we have done and what has been happening around us; by predicting where trends are heading and do all this by exploiting data we already have, tools we already own and brains that have not yet been put into deep freeze.
This all sounds good. Lets get started, "as soon as the movement hits critical mass".
IS there anyone out there already using BI?
When the first great era of commercial computing began, there were early adopters and late adopters. The early adopters paid for all the R&D (as usual) and the tail-draggers paid with loss of market-share, employee job satisfaction and investor confidence. Well, not really; business and consumers were not so hurried, cost conscious or quick to change horses back then.
Today is a different story, however. Deals are canceled at contract signing, shoppers abandon their carts at the check-out, construction is halted on the first foreclosure and stock market indicators have not seen a flat line in years. Panic is the normal state-of-rest.
Businesses sink quickly and everyone is hoping that the next object that floats by will have an outboard motor, wings and booster rockets attached. One such vehicle is that broad set of capabilities currently flying under the banner of Business Intelligence.
Many companies have made a leap of faith and invested in a BI initiative. For some of those entities, valuable gains have been achieved. For others, the project has been fruitless, hard lessons learned and second attempts made from a different approach.
Compared to the early data processing efforts, today's BI ventures are light years more advanced and equally more challenging. The potential for success is there for all qualified entrants and many have proved the point. Eventually, the deployment of BI will be as ubiquitous as the first generation of applications.
Just as every organization has implemented "passive" record-keeping applications of some sort or another, there will be a time when most will also have "active", even "thinking" intelligent software that examines data, sniffs out issues, evaluates propositions, recommends actions and monitors results. If you detect a difference in those two scenarios, you are understanding the meaning of Business Intelligence.
There was a time when computers were depicted in entertainment media as futuristic and the stuff of science fiction. Now we can smile at all of that and, yes, there are differences between what novelists and screenwriters created and the more mundane, however clever, computers that support every aspect of our lives today.
Don't forget, however, that the likes of HAL, C3P0 and R2D2 are seen in laboratories where artificial intelligence and other far-out technologies are constantly making progress. In our business world, we are not looking to replace people with thinking software, but with BI we can get people thinking better (with software).
BI may not be required or mandated for every type of organization; nor is it for the faint-of-heart; nor is it for the uninitiated (i.e. Those not understanding the issues). The separate MeasureGroup™ publication "Who needs BI?" can help an organization decide if it should, or should not, be looking at a BI initiative.
A summary of Business Intelligence
The following panel contains a summary of Business Intelligence in the form of a bullet list of the most significant attributes generally being assigned to this new but not-so-new technology that is going to be recognized one day as the "second great era of computing in business".
Summary of the key aspects of Business Intelligence:
- Leveraging Data Assets to glean Insights otherwise unavailable
- Exploring Business Analytics in an almost endless variety of ways
- Gaining Competitive Advantage thru the Power of Knowledge
- Seizing Opportunities to improve Status and Profitability
- Enhancing Business Agility - First to Start - First to Finish
- Using Intelligent Questions to generate Intelligent Answers to generate Intelligent Questions...
- Enabling Proactive Management to replace Reactive Damage Control
In the early days of computers, many did not see a use for them. That was because they did not yet understand their capabilities. BI is at that same point now. BI is being enabled by a new set of software tools and technologies that are continuing to evolve.
MeasureGroup™ is an operating division of dacc limited a software house that has box-product software sales exceeding 40,000 units to date and provider of consulting services to many of the world's best known companies across Europe and the United States.
Co-founder, president and CEO, Derek A. Ashton is a career professional with more than forty years of IT experience. He was the designer of the world's first ATM for TSB Bank (now Lloyds). Also an acknowledged expert in Software Quality Engineering, Mr. Ashton has spoken to audiences at major venues on Software Process Improvement and is SEI (Software Engineering Institute) trained and certified as a CMM Assessor (Capability Maturity Model) and Software Process Designer. Derek worked directly on all of the company's Data Warehouse assignments, either in a leadership role or as the DW Architect, covering a span of over 10 years.
"Our focus today is entirely on Data Warehouse and Business Intelligence development" is the word from Mr. Ashton. "The economic climate of late dictates corporations pay much more attention to the messages hidden within the mountains of accumulated but unexploited data they possess. Their future may depend on it, so there is no time to lose. However, those companies who diligently pursue potentially massive cost savings with their BI initiative are the ones who will quickly come out on top."
- Inadequate integration knowledge on Business Intelligence and Decision Support System Level. Dashboards are not good solutions.
- Not seeing complete Business Intelligence picture.
- No vision of what is final goal of BI tool. What are final outcomes and how will they be used for company prosperity and competitive advantage.
- Demands are created faster than Management Information Systems can absorb, implement and stabilize = Generating to big cumulated requests.
- No or little relation between financial statements and non financial key performance indicators.
- Lack of integrative systems in Legacy level.
- No or inadequate Mater Data Management solutions.
- No or inadequate Data Quality processes.
- Minimizing data quality issues by customer.
- Too high expectations from Business Intelligence. It is not an Expert System.
- Business Intelligence solutions are specialised. Can not cover everything.
- Out of the box solutions cover minor part of your current process and required functionalities. Be prepared to change processes more then to customize out of the box solution.
- Too dynamic complex market, like telecommunications.
- No internal technical knowledge on management and on expert level
- No internal dedicated team of experts to cooperate with vendors.
- No internal resources to handle knowledge generation.
- No internal structure to handle development of Business Intelligence layer.
- Wrong project lead.
- Too many internal enemies.
- Too ambitious management.
- Too naive management and project lead.
- Wicked management. Political games can destroy any project.
- Political games on management level. It is easy to declare "not needed any more".
- Lack or inadequate internal marketing.
- Wrong scheduling of modules. What comes first, next and at the end matters.
- Too long implementation time. Many other projects with significant impact happen during implementation time. Each impact could mean new code writing and starting from beginning in certain segments.
- Wrong vendor selection.
- Selection of wrong software solutions.
- Not enough resources to finish project. Especially in cases of additional costs that can double or triple initial investment.
- Lack of data definition or poor methodology.
- Too little integration with comptrolling. Comptrollers stay in their world with separated solutions.
- Internally made solution, more likely to fail than vendors solution.
- There is no one stop shop vendor solution. Each solution should be compared with leader in particular segment.
- Business Intelligence project should evolve.
- Can outsource the whole thing. Company must avoid the temptation of outsourcing everything and only things that are not core competences.
- Just give me the dashboard. Companies must have a solid and stable BI infrastructure before implementing dashboards.
- Information chasm between financial and non financial systems is too big.
- Inadequate consultancy.
- Trusting consultants too much.
- Start with internal development without asking users what they need.
- Mega requesting appetite. Data Warehouse/BI must cover all requests without any exemptions.
- Include all departments and business units, especially call on workshops as many people as possible. Nobody should say later that was not informed. Some call it spam with project but don't believe to gossips.
- Jumping into BI and Data Warehouse project without own IT administrators. Why should you have them since it is out of the box solution.
- Leave all operative work to consultants.
- Believing without any doubt to presented models and presentations of vendors.
- Scheduling and starting in parallel major upgrades of legacy systems.
- Not giving up from processes and not willing to change them.
- Modifying project scope and making false promises just to enter into company.
- Insufficient customer specification and lack of vendors notification about it.
- Staying too tight to signed specification. Not allowing single change.
Investments in the Business Intelligence area grow above average in relation to other management areas, and this favors the increase in demand for professionals with specific training in this area within the digital economy.
This program will allow you together in a discipline that effectively integrates business strategy, technology and processes to transform scattered data into knowledge and effective processes. Without doubt, a unique opportunity to learn to minimize business risks and managing organizations to intelligently and innovatively.
The Executive Program for Business Intelligence is aimed at IT managers and operations, sales and marketing, financial and consulting managers who wish to pursue an innovative approach of using data and information in an analytical way. The program tries to show, through the study of actual experiences, a new way to solve management problems. This course is organized in collaboration with the company, Business & Intelligence
The Executive MBA program is aimed at working professionals with a minimum of five years of professional experience from very different industries and areas of professional dedication who wish to deepen and advance their knowledge, skills and management skills to successfully address the challenges and challenges presented with the professional environment.
Proper management of organizations, regardless of their size and scope of economic activity goes through the effective management of projects that generate and execute it. And moreover if these actions take place in an international setting, where in addition to cultural diversity may influence other factors such as generation, companies need to have professionals with the skills and adaptability required to address different situations.
The Executive Programs in Project Management provides participants with an overview of management and project management at the sect oral level from a global perspective and facilitates an understanding of the innovative techniques and technologies for the development of management skills.
This executive program prepares you to obtain PPM certification, and is a fundamental tool for managing developments in the financial and human resources management.