Wednesday, July 27, 2016
Big Data is an ever-evolving term which is used to describe the vast amount of unstructured data. Published reports have indicated that 90% of the world’s data was created during the past two years alone.
Whether it’s coming from social media sites such as Twitter, Instagram, or Facebook, or from countless other Web sites, mobile devices, laptops, or desktops, data is being generated at an astonishing rate. Making use of Big Data has gone from a desire to a necessity. The business demands require its use.
Big Data can serve organizations in many ways. Ironically, though, with such a wealth of information at a company's disposal, the possibilities border on the limitless, and that can be a problem. Data is not going to automatically bend to a company's will. On the contrary, it has the potential to stir up organizations from within if not used correctly. If a company doesn't set some ground rules and figure out how to choose the appropriate data to work with, as well as how to make it align with the organization's goals, it's unlikely to get anything worthy out of it.
There are three layers of Big Data analytics, two of which lead to insights. The first of these, and the most basic, is descriptive analytics, which simply summarize the state of a situation. They can be presented in the form of dashboards, and they tell a person what's going on, but they don't predict what will happen as a result. Predictive analytics forecast what will likely happen, prescriptive analytics guide users to action. Predictive and prescriptive analytics provide insights.
Presenting the analytics on a clean, readable user interface is vital but sometimes is ignored. Users get frustrated when they see content that they can't decipher. A canned dashboard does not work for users. They need to know what action they have to take. Users demand a sophisticated alert engine that will tell them very contextually what actions to take.
Using such analytics, ZestFinance was able to glean this insight: those who failed to properly use uppercase and lowercase letters while filling out loan applications were more likely to default on them later on. Knowing this helped them identify a way to improve on traditional underwriting methods, pushing them to incorporate updated models that took this correlation into consideration. As a result, the company was able to reduce the loan default rate by 40% and increase market share by 25%.
Unfortunately, insights have a shelf life. They must be interpretable, relevant, and novel. Once an insight has been incorporated into a strategy, it's no longer an insight, and the benefits it generates will cease to make a noticeable difference over time.
Getting the Right Data
To get the right data leading to truly beneficial insights, a company must employ a sophisticated plan for its collection. Having a business case around the usage of data is the first important step. A company should figure out what goals it would like to meet, how and why data is crucial to reaching them, and how this effort can help increase revenue and decrease costs.
Data relevance is the key and what is important to a company is determined by the problems it is trying to solve. There is useful data and not useful data. It is important to distinguish them and weed out not useful data. Collecting more than what is useful and needed is impractical.
Often data is accumulating before a set of goals has been outlined by stakeholders. It is being collected irrespective of any specific problem, question, or purpose. Data warehouses and processing tools such as Hadoop, NoSQL, InfoGrid, Impala, and Storm make it especially easy for companies to quickly attain large amounts of data. Companies are also at liberty to add on third-party data sources to enrich the profiles they already have, from companies such as Dun & Bradstreet. Unfortunately, most of the data, inevitably, is irrelevant. The key is to find data that pertains to the problem.
Big Data is nothing if not available, and it takes minimal effort to collect it. But unfortunately, it will not be of use to anyone if it’s not molded to meet the particular demands of those using it. Some people are under the impression that they are going to get a lot of information simply from having data. But businesses don’t really need Big Data - information and insight are what they need. While a vast amount of data matter might be floating around in the physical and digital universes, the information it contains may be considerably less substantial.
While it might seem advisable to collect as much information as possible, some of that information just might not be relevant. Relevant insights, on the other hand, allow companies to act on information and create beneficial changes.
It is a good idea to set parameters for data collection by identifying the right sources early on. It could be a combination of internal and external data sources. Determine some metrics that you monitor on an ongoing basis. Having the key performance indicators (KPIs) in place will help companies identify the right data sources, the types of data sources that can help solve their problems.
Technology plays a key role in harnessing Big Data. Companies should figure out what kinds of technology make sense for them. Choice of technology should be based on company's requirements.
Data collection is an ongoing process that can be adjusted over time. As the business needs change, newer data sources are integrated, and newer business groups or lines of businesses are brought in as stakeholders, the dynamics and qualities of data collection will change. So this needs to be treated not as a one-time initiative, but as an ongoing program in which you continually enrich and enhance your data quality.
Companies should continually monitor the success of their data usage and implementation to ensure they're getting what they need out of it. There should be a constant feedback stream so that a company knows where it stands in relation to certain key metrics it has outlined.
Companies must always be aware of the risks involved in using data. Companies shouldn't use prescriptive analytics when there is significant room for error. It takes good judgment, of course, to determine when the payoffs outweigh the potential risks. Unfortunately, it's not always possible to get a prescriptive read on a situation. There are certain limitations. For one thing, collecting hard data from the future is impossible.
People and Processes
Big Data adoption often becomes a change management issue and companies often steer clear of it. When a company implements something that's more data-driven, there's a lot of resistance to it.
Like most initiatives that propose technology as a central asset, Big Data adoption can create conflicts among the various departments of an organization. People struggle to accept data, but people also aren’t willing to give it up. To avoid such clashes, companies should make it clear from the outset which department owns the data. Putting the owner in charge of the data, having this person or department outline the business rules and how they should be applied to customers would be helpful to overcome this issue.
These are two good tips to follow: Give credit where credit is due and don't dehumanize the job. Don’t attribute the success to the data, but to the person who does something with the data. Remember that change can't just come from the top down. Big Data adoption requires more than executive support. It needs buy-in from everyone.
Saturday, July 23, 2016
It is getting more unlikely to find paper documents in filing cabinets or electronic documents in shared network drives. Filing cabinets and shared network drives have been replaced by content management systems, knowledge base application, and collaboration tools in majority of organizations.
At a certain point, it's inevitable that organizations have to make adjustments to keep up with the times. users must constantly adapt to the tools of an evolving world. After all, if customers are using advanced technology, it makes sense that companies should be interacting with them using tools that are up to date as well.
If technology adoption is to have an effect on an organization, users' commitment becomes a required element. But getting that kind of cooperation is not always a simple task. Users might not immediately take to the new processes without some resistance.
Though it's counter-intuitive that anyone would resist technology designed to make their job easier, the resistance is unavoidable element of content and knowledge management initiatives. Organizations should anticipate a number of challenges and do their best to ease their users's resistance through the transition and change management.
Drawing from our 16 years of experience successfully managing user adoption and change management in content and knowledge management initiatives, these are our guidelines for organizations to overcome challenges in these areas.
1. Communicate the Goals
There may be myriad practical reasons for why the change in how your organization manages its content needs to be put in place. Before proposing any major change, establish clear reasons for why the change is being proposed, and how it is going to enhance users' experience.
For users to understand how technology is going to help them, they need to understand what their future will look like with this technology in place. What it amounts to is if you can't articulate the benefits of making the change, you have no business of making this change.
It is very important to create a consistent narrative that instills confidence in users as well as the language you use to deliver this narrative to users. Avoid using the term "change management". The reason is that employees hear "change management" as "Whatever you have done until now is wrong, and now we are going to put you on the right track." That is not a good message.
You may want to use the term "cause management" which attributes any need for adjustment within a company to a cause. Under this approach, organizations would make an effort to craft a story that communicates the idea that this is the outcome that will best benefit the company.
Highlighting what is not going to be changing can be a source of encouragement for users. This way you are introducing a consistency while asking users to evolve.
2. Fear of Change is not Necessarily Fear of Technology
Technology itself is not usually the reason that employees are resistant to change. People are becoming less resistant to using technology. Problems begin to surface when employees are not given enough notice about what technology they are expected to use.
Even before it's been decided which technology organizations have settled on, organizations should give their employees an outline of the problems they are trying to fix. This would give them the opportunity to provide input and make suggestions about what types of processes they would like to see streamlined and how they envision their ideal work environment. Though organizations might not always have the budget for what the employees have in mind, they will at least be involving them and making them feel as though they are part of the equation from the outset.
Also important is that workers are given the time to develop the kinds of skills necessary to make full use of technology. It takes employees some conditioning to see how new technology and procedures can be of aid to them. If you can be proactive about teaching people these new skills and how to use the technology in small segments, this definitely can accelerate the change.
3. New Technology Can Bruise the Ego
All employees are proud of their work. They like to feel as though they possess an innate talent, and that there's a reason they're doing what they've chosen to dedicate so much of their time to. Regardless of age or experience level, there are certain natural emotions that might come into play when companies are proposing changes. If employees are led to believe that so much of what they spent a great deal of time mastering can be transferred to anyone with an ease, they might resent it on an emotional level that they might not even share.
Thus, it would be a good idea to communicate how the technology is going to help them work together and be more connected.
4. Technology is not Only for Managers
It goes without saying that technology should never force people to do more work than they are already doing. If you force people to use a system that is making their jobs worse, they' are going to do everything they can to avoid it.
Employees should never feel as though technology is being deployed solely for the benefit of the managers. Granted, content management system provides managers with more visibility into work processes, but the central message managers should be sending is that the technology is there to help employees do their jobs better.
It is helpful to illustrate that higher management is using the technology as well, for the sake of driving home the idea that the technology is being universally adopted by the organization.
5. Deploy Gradually
When it comes to deploying the systems that employees are going to be using regularly over an extended period of time, it is a good idea to steer clear of an abrupt implementation in favor of a more gradual one.
Use Pilot Periods. During these periods, a small subset of the company is selected to test the technology and share its experiences with the others. Keeping employees updated via email, meetings, or through other internal communication channels can be helpful, as it also lets people know what to expect. Likewise, getting user testimonials and videos in which those who have piloted the product attest to its benefits could prove useful.
However, it's important to be all-inclusive when deciding who is going to be participating in such trial periods. While it might be tempting to recruit the most enthusiastic and vocal representatives of a company to test the materials, it might be a better idea to go for a mix to act as testers. Use a subset of users that will represent those who are ultimately going to be expected to use the new technology. Of course, asking volunteers to step forward is advised, but testers should also be drawn from a segment of those who are not as keen on trying it.
Including people who are not technology experts is a good idea, because it helps drive home the point that anyone can use the solution effectively. It also reinforces the idea that there will be support and training opportunities available.
If the right group of people is selected for the pilot program, they can generate excitement about the system and show how the program has helped them do their jobs.
One small factor to keep in mind about the pilot period, however, is the capacity of the system. Since the entire program will eventually be inhabited by more users, the experience that the small subset reports might differ from the one that is waiting further down the line. For example, a system that works fine when you have ten users on it may not work as quickly when there are 200,000 users connected to it. You need to be able to account for things like that.
6. Maintain the Change
Change management is not as simple as preparing employees for the transition that is about to be introduced. It has just as much to do with ensuring that employees don't revert to outdated and inefficient methods as it does with ensuring that people begin to use it. Managing resistance is a process, not a series of events.
Because it's a process, managers should be very careful to communicate the fact that the improvements might not come all at once, but rather in small increments. Incentives can also act as fruitful aids in encouraging adoption. For this very reason, gamification applications have been gaining popularity because they allow employees to compete against one another and display to the rest of the company how well they have done by showing off their achievements.
It is important to build employees confidence and a positive environment. Set specific event days to encourage the use of the new technology. Typically held once a month, these are known as blitz days. The idea is to set aside a time period during which everybody is forced to use the technology in a fun environment. At the end of the day, the users share those results. The goal is to say that if this can be done on one particular day, why can't it be done every day? Over time, the benefits of these events could be substantial.
Change is ongoing. As time goes on, the window for change for technology is becoming much narrower than it used to be, with updates occurring far more frequently. For some people, it might seem that just as they are getting used to one change, another one is on the way. Organizations need to create an infrastructure that better supports that.
Characteristics for Driving Change
- Be outwardly focused - avoid being locked into one area of the company. Look for ways to make an impact across organizations.
- Be Persuasive - be clever and persuasive enough to gain the support of users.
- Be Persistent - do not give up. Constantly work through the channels of the organization to ensure that new systems and processes are factored into organizations' way of work.