Due to the ever quickening pace of modern business, users of business intelligence demand faster access to the data they use to make critical business decisions. By streamlining access to information, smaller business can enable employees to access fresher data that informs real-time decisions and become more responsive and nimble than larger organizations
Historically, the data warehouse was a back-office application used by very few people for “after-the-fact” analysis and planning that are the core of business intelligence. For example, a business analyst or senior level manager would run trending reports on sales revenue for previous years and evaluate sales peaks, valleys, and patterns correlating to a particular season or external economic factor. Based on the results, they would make recommendations on future sales and marketing strategies.
But that takes too long for today’s ever-quickening business climate. Now, users across organizations must be empowered to make hundreds of small decisions each day; data is accessed by more and more people as front line sales and call center representatives arm themselves with the most recent information so they can act. It’s not acceptable to tell a distressed customer that you will return their call tomorrow or ask them to provide the same information repeatedly as they move through a phone tree.
Smaller business can gain a real competitive advantage by unlocking analytical systems to enable employees access to fresher data that informs real-time decisions. Large enterprises see this opportunity as well and that’s led business and IT leaders to reassess their data warehouse strategies to streamline the way organizations leverage information with the goal of optimizing workflow, productivity, and decision-making capabilities. The BI mantra is no longer “sense and respond,” but rather “anticipate, predict, and prevent,” with data-based confidence.
CHASING A SINGLE VERSION OF THE TRUTH
BI is a high priority: to know your customer is to know your business. In reality, this may not only require a comprehensive view of the customer, but also a comprehensive view of suppliers, partners, and revenue by product or channel. Gaining a fully integrated and relevant view of a piece of your business poses an ongoing IT challenge. The changes that come with a growing business — mergers, acquisitions, new products, services, and markets — only compound the ordeal.
A single version of the truth that is accurate and up to date has become the Holy Grail of BI. Business decision makers and end users know achieving that single view based on current data helps avoid making erroneous decisions, saving a company valuable time and resources. Harnessing the power of BI data can help small and midsize organizations compete by allowing them to be more agile and responsive to customers and partners than large enterprises with greater budgets and resources. Having a clear understanding, a single truth, of how the business is performing right now is key to moving forward and staying competitive — redefining the customer experience and expectation.
Access to both historical and current data enables a business to spot trends as soon as they begin to occur and make decisions to “stay the course” or, more important, correct course. For example, an online retailer running a promotional campaign may have a market segment that is particularly responsive. With access to that information in real time, the retailer can quickly decide to extend the life of the special offer or introduce it to another market segment, driving a timely revenue up-tick — not unlike what many shop-at-home networks do today.
The online specialty retailer also may be able to win sales over a national or multinational chain because it can provide a tailored customer experience. Consumers, becoming more fickle by the day, respond to personalized service and may not only choose to buy from the retailer today, but also in the future. A single view of the customer would enable the company to recognize immediately what buying preferences it should repeat to create that positive experience in multiple sales channels (i.e., Internet, catalog, or retail).
In the brick-and-mortar world offline, better BI also drives revenue. Independent grocery stores, for example, must keep up with large national chain supermarkets to survive, particularly in a consolidating market. With millions of weekly transactions, feeding fresh point of sale data to a data warehouse in real time reduces delays and risk of transmission errors. The independent grocery also can make real-time decisions based on sales by store or by department for any given item. Relatively small changes based on this information, such as marking an item up or down, can significantly affect revenue and allow stores to retain customers in a competitive market.
The central data warehouse, operational data store, or dedicated reporting server should enable business intelligence software access to current, accurate data. While ideally all users would query the same central repository, in many cases this information still resides in multiple systems, creating redundant copies of the same data. It’s important to ensure that business information is consistent, regardless of when, where (which system), how, and by whom it is queried. Data integrity and the ability to reconcile information is a key part to a sound BI strategy and fundamental to maximizing the value of your investment.
Many growing businesses face IT diversity, which could be the result of system consolidation or acquisitions, creating new challenges for data management. To achieve data integration, an organization needs to define the rules of coexistence for the source and reporting assets — logically and physically.
For example, a finance team may keep customer information in one system, while sales has a separate repository with data about the same customer. The challenge with redundancy is that reporting from both systems can produce two very different answers. Enabling these systems to “talk to one another” is a challenge that most organizations face regardless of size.
Added to this challenge is the speed at which business moves and changes. A major success factor is to create an effective integration strategy across a diverse technology portfolio. Developing custom code to enable data to move from one environment to another is often a less expensive approach, but only initially. As that environment changes with new versions and functionality, the integration code needs to change with it, adding layers of complexity, and tying up expensive IT resources.
In a tight budget environment, many smaller businesses sensibly standardize on one product or approach to integration across different systems. There are numerous infrastructure technologies that can be easily deployed to show a fast ROI without consuming a large number of existing IT resources. The “Big Bang” theory of everyone standardizing on one infrastructure platform may not appear feasible, but if you rationalize on a targeted basis, you will be better positioned to define the right level of standardization for your enterprise.
Active BI can be a lofty term, full of promise and possibility, but at the same time daunting for businesses wrestling with budgets. This leads to the customary scratching of the head as to how to yield more value from systems already in place — including speed, flexibility, and integrity of the data flowing into and out of the analytical and reporting system. Whether your business has 10 employees or 1,000, the same three key tenets of “intelligent” BI can put you on the road to success.
1. Integrate data from diverse source systems into a single version of the truth and eliminate redundancy when you can.
2. Provide the warehouse with low-latency data so users can access the most current information and can make good decisions.
3. Provide the necessary level of availability and recoverability for your data warehouse and BI systems as the business comes to rely upon it.
THE INTELLIGENT CHOICE: BRINGING IT ALL TOGETHER
Given the diversity source systems, many organizations are hesitant to invest in standardization. However, some standardization is integral to pursuing more active, agile BI. The areas of conversion cost, change management, operating risk and current asset value all need to be taken into consideration as you assess your goals for standardization.
Standardizing on certain technologies within your BI stack can pay off — but with integration challenges in mind, neutrality is key. Choose technologies that support the widest range of databases, hardware platforms, and operating systems, so that you increase the lifespan and relevancy of your investment.
A concluding point; in raising the bar for BI, the data is crucial — because without the most up-to-date information, your business will always remain a few steps behind. Gone are the days when data warehouses were just used for after-the-fact historical reporting and long-term forecasting. Today, companies are working hard to make the data warehouse or analytical system more operational, and more accessible by multiple functions of the business, thus making the business itself more intelligent.
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