Which KPI?s to Use in CRM

Customer relationship management emerged in the 1980?s in the form of database marketing. In those tranquil pre-social media days, the possibility of ?managing? clients may have been a possibility although Twitter and Facebook took care of that. Modern managers face a more dynamic environment. If you are one, then what are the trends you should be monitoring yourself (as opposed to leaving it to others).

If you want to drip feed plants, you have to keep the flow of liquid regular. The same applies to drip-feed marketing. Customers are fickle dare we say forgetful. Denizon recommends you monitor each department in terms of Relationship Freshness. When were the people on your list last contacted, and what ensued from this?

Next up comes the Quality of Engagements that follow from these efforts. How often do your leads respond at all, and how many interfaces does it take to coax them into a decision? You need to relate this to response blocks and unsubscribes. After a while you will recognise the tipping point where it is pointless to continue.

Response Times relate closely to this. If your marketing people are hot then they should get a fast response to sales calls, email shots and live chats. It is essential to get back to the lead again as soon as possible. You are not the only company your customers are speaking too. Fortune belongs to the fast and fearless.

The purpose of marketing is to achieve Conversions, not generate data for the sake of it. You are paying for these interactions and should be getting more than page views. You need to drill down by department on this one too. If one team is outperforming another consider investing in interactive training.

Finally Funnel Drop-Off Rate. Funnel analysis identifies the points at which fish fall off the hook and seeks to understand why this is happening. If people click your links, make enquiries and then drift away, you have a different set of issues as opposed to if they do not respond at all.

You should be able to pull most of this information off your CRM system if it is half-decent, although you may need to trigger a few options and re orientate reporting by your people in the field. When you have your big data lined up speak to us. We have a range of data analysts brimming over with fresh ideas.

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How Alcoa Canned the Cost of Recycling

Alcoa is one of the world?s largest aluminium smelting and casting multinationals, and involves itself in everything from tin cans, to jet engines to single-forged hulls for combat vehicles. Energy costs represent 26% of the company?s total refining costs, while electricity contributes 27% of primary production outlays. Its Barberton Ohio plant shaved 30% off both energy use and energy cost, after a capital outlay of just $21 million, which for it, is a drop in the bucket.

Aluminium smelting is so expensive that some critics describe the product as ?solid electricity?. In simple terms, the method used is electrolysis whereby current passes through the raw material in order to decompose it into its component chemicals. The cryolite electrolyte heats up to 1,000 degrees C (1,832 degrees F) and converts the aluminium ions into molten metal. This sinks to the bottom of the vat and is collected through a drain. Then they cast it into crude billets plugs, which when cooled can be re-smelted and turned into useful products.

The Alcoa Barberton factory manufactures cast aluminium wheels across approximately 50,000 square feet (4,645 square meters) of plant. It had been sending its scrap to a sister company 800 miles away; who processed it into aluminium billets – before sending them back for Barberton to turn into even more wheels. By building its own recycling plant 60 miles away that was 30% more efficient, the plant halved its energy costs: 50% of this was through process engineering, while the balance came from transportation.

The transport saving followed naturally. The recycling savings came from a state-of-the-art plant that slashed energy costs and reduced greenhouse gas emissions. Interestingly enough, processing recycled aluminium uses just 5% of energy needed to process virgin bauxite ore. Finally, aluminium wheels are 45% lighter than steel, resulting in an energy saving for Alcoa Barberton?s customers too.

The changes helped raise employee awareness of the need to innovate in smaller things too, like scheduling production to increase energy efficiency and making sure to gather every ounce of scrap. The strategic change created 30 new positions and helped secure 350 existing jobs.

The direction that Barberton took in terms of scrap metal recycling was as simple as it was effective. The decision process was equally straightforward. First, measure your energy consumption at each part of the process, then define the alternatives, forecast the benefits, confirm and implement. Of course, you also need to be able to visualise what becomes possible when you break with tradition.

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What Kanban can do for Call Centre Response Times

When a Toyota industrial engineer named Taiichi Ohno was investigating ways to optimise production material stocks in 1953, it struck him that supermarkets already had the key. Their customers purchased food and groceries on a just-in-time basis, because they trusted continuity of supply. This enabled stores to predict demand, and ensure their suppliers kept the shelves full.

The Kanban system that Taiichi Ohno implemented included a labelling system. His Kanban tickets recorded details of the factory order, the delivery destination, and the process intended for the materials. Since then, Ohno?s system has helped in many other applications, especially where customer demand may be unpredictable.

Optimising Workflow in Call Centres
Optimising workflow in call centres involves aiming to have an agent pick up an incoming call within a few rings and deal with it effectively. Were this to be the case we would truly have a just-in-time business, in which operators arrived and left their stations according to customer demand. For this to be possible, we would need to standardise performance across the call centre team. Moving optimistically in that direction we would should do these three things:

  • Make our call centre operation nimble
  • Reduce the average time to handle calls
  • Decide an average time to answer callers

When we have done that, we are in a position to apply these norms to fluctuating call frequencies, and introduce ?kanbanned? call centre operators.

Making Call Centre Operations Nimble
The best place to start is to ask the operators and support staff what they think. Back in the 1960?s Robert Townsend of Avis Cars famously said, ?ask the people ? they know where the wheels are squeaking? and that is as true as ever.

  1. Begin by asking technical support about downtime frequencies, duration, and causes. Given the cost of labour and frustrated callers, we should have the fastest and most reliable telecoms and computer equipment we can find.
  1. Then invest in training and retraining operators, and making sure the pop-up screens are valuable, valid, and useful. They cannot do their job without this information, and it must be at least as tech-savvy as their average callers are.
  1. Finally, spruce up the call centre with more than a lick of paint to awaken a sense of enthusiasm and pride. Find time for occasional team builds and fun during breaks. Tele-operators have a difficult job. Make theirs fun!

Reducing Average Time to Handle Calls
Average length of contact is probably our most important metric. We should beware of shortening this at the cost of quality of interaction. To calculate it, use this formula:

Total Work Time + Total Hold Time + Total Post Call Time

Divided By

Total Calls Handled in that Period

Share recordings of great calls that highlight how your best operators work. Encourage role-play during training sessions so people learn by doing. Publish your average call-handling time statistics. Encourage individual operators to track how they are doing against these numbers. Make sure your customer information is up to date. While they must confirm core data, limit this so your operators can get down to their job sooner.

Decide a Target Time to Answer Calls
You should know what is possible in a matter of a few weeks. Do not attempt to go too tight on this one. It is better to build in say 10% slack that you can always trim in future. Once you have decided this, you can implement your Kanban system.

Introducing Kanban in Your Call Centre Operation
Monitor your rate of incoming calls through your contact centre, and adjust your operator-demand metric on an ongoing basis. Use this to calculate your over / under demand factor. Every operator should know the value on this Kanban ticket. It will tell them whether to speed up a little, or slow down a bit so they deliver the effort the call rate demands. It will also advise the supervisor when to call up reserves.

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A Definitive List of the Business Benefits of Cloud Computing ? Part 4

Lowers cost of analytics

Big data and business intelligence (BI) have become the bywords in the current global economy. As consumers today browse, buy, communicate, use their gadgets, and interact on social networks, they leave in their trail a whole lot of data that can serve as a goldmine of information organisations can glean from. With such information at the disposal of or easily obtainable by businesses, you can expect that big data solutions will be at the forefront of these organisations’ efforts to create value for the customer and gain advantage over competitors.

Research firm Gartner’s latest survey of CIOs which included 2,300 respondents from 44 countries revealed that the three top priority investments for 2012 to 2015 as rated by the CIOs surveyed are Analytics and Business Intelligence, Mobile Technologies, and Cloud Computing. In addition, Gartner predicts that about $232 million in IT spending until 2016 will be driven by big data. This is a clear indication that the intelligent use of data is going to be a defining factor in most organisations.

Yet while big data offers a lot of growth opportunities for enterprises, there remains a big question on the capability of businesses to leverage on the available data. Do they have the means to deploy the required storage, computing resources, and analytical software needed to capture value from the rapidly increasing torrent of data?

Without the appropriate analytics and BI tools, raw data will remain as it is – a potential source of valuable information but always unutilised. Only when they can take the time, complexity and expense out of processing huge datasets obtained from customers, employees, consumers in general, and sensor-embedded products can businesses hope to fully harness the power of information.

So where does the cloud fit into all these?

Access to analytics and BI solutions have all too often been limited to large corporations, and within these organisations, a few business analysts and key executives. But that could quickly become a thing of the past because the cloud can now provide exactly what big data analytics requires – the ability to draw on large amounts of data and massive computing power – at a fraction of the cost and complexity these resources once entailed.

At their end, cloud service providers already deal with the storage, hardware, software, networking and security requirements needed for BI, with the resources available on an on-demand, pay-as-you-go approach. In doing so, they make analytics and access to relevant information simplified, and therefore more ubiquitous in the long run.

As the amount of data continues to grow exponentially on a daily basis, sophisticated analytics will be a priority IT technology across all industries, with organisations scrambling to find impactful insights from big data. Cloud-based services ensure that both small and large companies can benefit from the significantly reduced costs of BI solutions as well as the quick delivery of information, allowing for precise and insightful analytics as close to real time as possible.

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