It’s always very telling how a company makes decisions. Are decisions made just based on anecdotal experience? Do you hear, “I always do X to solve Y,” “This is how we do X around here”? In companies like this, the importance of information-driven decisions is not recognized. There are mountains of data, but leadership often doesn’t realize the value that can be harnessed from information.
The quotation, “Those who cannot remember the past are condemned to repeat it” is certainly applicable to businesses. In order to identify good and bad decisions, organizations have to examine the past to either repeat the things they did well or avoid things they didn’t. So, reflection is a requirement for learning.
For instance, if we look at the advancements in health care delivery, evidence-based medicine comes to mind. With evidence medicine in practice, a patient’s medical history (and not just the presenting symptoms), efficacies of clinical pathways and treatment types are all collated, and the most relevant and appropriate treatment is delivered, all based on scientific evidence, not just a clinician’s bias or preference.
This is only possible in an organization that has made a commitment to learning. An organization committed to learning doesn’t punish mistakes, but it punishes repeating them. Consider the realm of big pharmaceuticals. The time and cost to bring a new drug to the market typically amount to at least 12 years and about a billion dollars. Many drugs that fail in late stages of a four-phase clinical trial may have shown signs all the way. Some leading pharmaceuticals reward employees who are forthright in reporting potential failures early in the process and who also record and share that information with their colleagues. These companies build knowledge on leading practices and document and learn about missteps along the way.
On the flip side, success is usually celebrated within a company but not dissected. How does the company consistently make good decisions? Providing and sharing the context in which decisions were made sheds more light on the successes, making it easier to identify ways to replicate those good decisions across the company. With the advent of intranet wikis and social networking tools used within the enterprise, it’s a missed opportunity if companies don’t share information throughout the company. This is not a technology imperative, but is more a function of an adaptive and learning culture within the company.
Enterprise portals play a key role in such organizational learning. Integrating information from operational systems, business intelligence reports, project documents and leading practices so it is searchable makes it very powerful for future use. Search engine technology is getting progressively better at fine-tuning searches and tuning out noise. These search engine advances eventually will make their way into the corporate intranet as well.
In order to measure the effects of decisions, they have to be tracked. Decisions have to be surrounded by context to provide a complete picture of the circumstances under which they made. For instance, if there’s a restructuring within a company due to M&A or resulting from a new operating model, management would definitely want to pay particular attention to the execution of the strategy. With the ability to report on dimensional history as well as to report on multiple alternate hierarchies, we can deliver reports pre- and post-restructuring. Although the result is fairly indicative of performance (or lack of it), it doesn’t necessarily mean departmental/personnel shuffling was the cause. Business performance is impacted by external factors (like the economy, volatility in markets the company operates in, currency, etc.) and reasons internal to the organization, like a new performance metrics implementation within the company that may not be well aligned with the structural changes. These factors are not captured in any of our facts and dimensions. This area needs more advancement in thought, designs and technology platforms. (I will write more about this in a future article.)
Information Quality and Governance
Information provides context and insight to be able to make the right decisions. In order to make the right decisions, information not only has to be accurate but timely as well. This brings quality and governance to the forefront. Who in the business is in charge of information? Should the office of the CIO govern it as well? If a business truly understands the value of data/information, then getting the people responsible for specific business functions to own up to quality wouldn’t be a challenge. Too often, before we are able to articulate the value proposition of quality and governance, we delve into governance design and implementations. To demonstrate the value, sometimes it’s worth looking at use cases resulting from a lack of governance as well. Even when this perspective is initially established, reiterate the very important question, “How critical is accurate and timely information to your business?”
In order for information to be timely, it must be fluid. Information created within an enterprise is the cornerstone to all business strategies, and technology can enable business objectives. Enterprise resource planning systems enable almost every aspect of the business, providing operational efficiencies and opening up opportunities in many areas. Despite these technological advances, every IT or business executive you talk to immediately brings up the challenges they have on a day-to-day basis unlocking the information from an assortment of systems. In many cases, each of these systems does exactly what the system was procured to do in the first place. Many companies look to data warehouses to integrate the information across the enterprise to provide a single point of access. For these companies, challenges are tantamount, including adding new systems on the operational side, timeliness of access to information or changing business rules, new data meanings, new ways of looking at existing information and
new audiences within and outside the enterprise - which also presents challenges around performance, scalability and security.
Information Supply Chain
If you have an enterprise data warehouse and product packaging and pricing is loaded once a week, then your analysis around product bundles and price effectiveness cannot be any more recent than one week. If it is refreshed daily, then the velocity can be no sooner than one day. It is important to establish a minimum and maximum time, benchmarked against acceptable levels for each type of data/information that can flow through your system. It’s also important to see the numbers in the context of business requirements. As you’re preparing for this during the requirements phase, get real use cases out in the open to ensure that the data platform can support it.
The information fluidity can change on a continual basis - not just when there’s a major business or system-wide change. Everything from changing business rules, new technologies being implemented or increasing the size of the user community can all cause the velocity to change. Michael Dell, in his book “Direct from Dell” talks about how Dell’s business is empowered by a super agile information supply chain. There are many situations where information can be a source of competitive advantage, but not having it in a timely fashion can pose business risk, and in extreme cases, it can put lives at risk (like at a hospital or on the battlefield).
Today, most companies use some kind of reporting technology. If standardizing on a reporting toolset is a challenge for your organization, integrate information via a standard portal technology. Achieve information integration at the enterprise data warehouse layer as much as possible. For information to be accurate, it’s important for data to be surrounded by accurate metadata as well. Get your business to think about information beyond just reports. Too many companies engage in developing/migrating an inordinate number of reports, platform after platform. Continue to build and deliver information with self-service in mind. Self-service deserves further exploration in a future article, but in a nutshell, the semantic layer (metadata modeling) in a BI platform needs to be more robust and modeled for self-service.
In the next part of this series, we will look at how to obtain the right technology focus. To read part one of this series, click here.
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