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The business potential in the ‘nexus’ enabled market

In my post about the Gartner ‘nexus of forces’ my first point is to understand the business potential. Let me delve into this a bit more.

Social, mobile, cloud and data are the technology advances that together make up the current trend that will be changing the face of business. Each of these I analyze from different perspectives as to what these advances are and how they can be used.

As a nexus, how do we understand the potential to businesses? Imagine having much more comprehensive and linked data around your markets, your customers, the purchasing funnel, the products and services in your markets, and competitive data. Mobile activities and social media provides additional insights into all data, and cloud computing allows you to cost effectively store, process and analyze all. In real time you can be aware of market conditions changes or customer trends through your comprehensive analytic engine. In real time supply chain adjustments can be made, products can be shifted to new geographies, customers can be contacted with service, advertising can be targeted, or marketing offers can be presented at the right time in the purchasing decision.

Here are some items to stimulate thinking about the impact:

DATA

  1. Market data – what data is currently available in your market? Is it reference data that describes the fundamentals in the market? Market activity and transactions? In the financial markets the transactions are captured and compiled into indexes, but many markets do not have such transparency. Do you have access to proprietary data that if combined with other data provides insights into market flows and activities?
  2. Purchasing data – Can you capture or acquire data from several points in the purchasing funnel? When does your potential customer start considering a purchase, what are the research activities, how are products and services compared, how are the decisions made? Can we link this data to understand what culminates into a transaction?
  3. Customer data – CRM and order to cash systems should contain a lot of a business’ customer data, how about linking this with adjacent customer data from other industries?
  4. Product and service data – Is there usage or utilization data for your products and services? How about customer feedback data? Can the data be linked, and can real time feedback result in a customer service situation?
  5. Competitive data – Can the basic competitive data about products and services in your market be analyzed at a transactional detail level? By geography, customer or market segment? Is social media data available real time for new product introductions?
  6. Internal company data – often a wealth of data is available within your company, but it is not linked or utilized in real time analytic situations. For example, manufacturing companies often have great supply chain and manufacturing process data, do you have process data around the sales process, the order to cash process, or the customer service process. And if this is available, are you linking this data to understand the entire value chain at both the process and transaction level?

MOBILE

  1. Geo location – both individual data and aggregate information is very valuable. Real time capability to interact with an individual that is arriving, resident, or leaving a location provides many opportunities to enhance the experience of a customer or provide additional value.
  2. Apps – so there are some nifty apps out there, but I believe this is still in its infancy. Much more comprehensive data available through APIs will provide real-time, location dependent apps that connect to other adjacent devices (cars, fitness monitors, media etc.) and create capabilities that we haven’t experienced yet.
  3. Camera – The most popular use of snapshots has started to be complemented by use of location aware specific data. Visual recognition capabilities (i.e. what is in the picture) will become increasingly available and meta data produced in real time will increase the value of the camera. 
  4. New devices – most consider tablets and smartphones when discussing mobile, but a slew of new smart devices are starting to come on the market. Consider the COIN smart credit card, the TILE location monitor, AIRO fitness monitor with spectrometer capabilities, smart home devices and all these devices will be able to interact on a data level through apps.

SOCIAL

  1. Customer experience – Social media is rich with current customer experience and this feedback can be used to intercept situations or to enhance customer service experience.
  2. Product feedback – comments and thoughts about products are throughout social media, this data will continue to become more available. The value of passive feedback is great, and will impact product development, sales and customer service.
  3. Customer interaction – careful so as to not inappropriately interrupt or hijack the customer’s social activities, most brands can and should interact with customers and potential customers in social media.
  4. Awareness –  are your potential customers aware of your brand, you products or services? Beyond context aware advertising, which itself is making rapid advances, and interaction in social media, what other avenues are available to you to increase awareness?

CLOUD

  1. The cost of scalable computing – Both the cost and the scalability are of great importance. Forget about the technology itself for a second, accept that processing of transactions and other data can happen real-time or near real-time in a different expense paradigm. There will be a combination of reduced infrastructure expense and increased availability of computing, depending on needs.  Computing requirements will gradually become more standardized at the technology level and rely on ubiquitous computing availability. This will also enhance reliability and disaster recovery capabilities both of which are still significant challenges in the industry.
  2. Real time analytic engine – Analytic engines require significant compute power and rapid data systems, both of which become significantly more available in the cloud paradigm. New predictive analytic technology combined with the compute availability will shift capabilities from historical limited analytic systems that run on a daily or weekly basis to real-time or near real-time systems that have greatly enhanced data association and visualization strengths.
  3. One-time and ongoing operations – What we see today are the early applications in big data and analytic capabilities, and they mostly focus on the one-time analysis or data mining opportunity. This will evolve into operational capabilities that perform these functions on an ongoing basis.

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